From d029d5d7f8ead1f1de8d318045004a4a6f68f5fb Mon Sep 17 00:00:00 2001 From: Bonface Date: Fri, 9 Feb 2024 09:41:28 -0600 Subject: Update dataset RTF Files. --- general/datasets/INIA_AmgCoh_0311/cases.rtf | 3 + .../INIA_AmgCoh_0311/experiment-design.rtf | 1152 ++++++++++++++++++++ general/datasets/INIA_AmgCoh_0311/platform.rtf | 1 + general/datasets/INIA_AmgCoh_0311/processing.rtf | 16 + general/datasets/INIA_AmgCoh_0311/summary.rtf | 1 + general/datasets/INIA_AmgCoh_0311/tissue.rtf | 12 + 6 files changed, 1185 insertions(+) create mode 100644 general/datasets/INIA_AmgCoh_0311/cases.rtf create mode 100644 general/datasets/INIA_AmgCoh_0311/experiment-design.rtf create mode 100644 general/datasets/INIA_AmgCoh_0311/platform.rtf create mode 100644 general/datasets/INIA_AmgCoh_0311/processing.rtf create mode 100644 general/datasets/INIA_AmgCoh_0311/summary.rtf create mode 100644 general/datasets/INIA_AmgCoh_0311/tissue.rtf (limited to 'general/datasets/INIA_AmgCoh_0311') diff --git a/general/datasets/INIA_AmgCoh_0311/cases.rtf b/general/datasets/INIA_AmgCoh_0311/cases.rtf new file mode 100644 index 0000000..b02b19a --- /dev/null +++ b/general/datasets/INIA_AmgCoh_0311/cases.rtf @@ -0,0 +1,3 @@ +

Cases. A total of 58 strains, including 54 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1) were analyzed. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by K. Mozhui. Samples were pooled by sex and usually include at least two cases per sex and strain.

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Sex Balance. Fifty strains have matched male and female samples. Five strains have male only samples (BXD5, 13, 16, 100 and 103). Three strains have only female samples (BXD44, 70, and 87.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.

diff --git a/general/datasets/INIA_AmgCoh_0311/experiment-design.rtf b/general/datasets/INIA_AmgCoh_0311/experiment-design.rtf new file mode 100644 index 0000000..126d431 --- /dev/null +++ b/general/datasets/INIA_AmgCoh_0311/experiment-design.rtf @@ -0,0 +1,1152 @@ +

Data Evaluation Summary

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  1. eQLTs with LOD >10 (LRS>46.1): n = 525
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  2. eQTL with high LOD and LRS: Trait ID 10513604 (Hdhd3) LOD = 39.8, LRS = 183.5
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  3. Lowest mean value: Trait ID 10344361, mean = 3.998
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  4. Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
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  5. Greatest sex difference: Trait ID: 10606178 (Xist)
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  6. Great variation within and among strains: Trait ID 10454192 (Ttr +
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    IndexArray IDTissueStrainAgeSexDate sacrificeTime sacrifice
    1R6853BLBLAC57BL/6J77F8/18/108:45AM to 12:30 PM
    2R6861BLBLAC57BL/6J77M8/18/108:45AM to 12:30 PM
    3R6851BLBLAD2B6F177F8/18/108:45AM to 12:30 PM
    4R6859BLBLAD2B6F177M8/18/108:45AM to 12:30 PM
    5R6863BLBLADBA/2J77F8/18/108:45AM to 12:30 PM
    6R6865BLBLADBA/2J68M8/18/108:45AM to 12:30 PM
    7R6857BLBLAB6D2F169F8/18/108:45AM to 12:30 PM
    8R6855BLBLAB6D2F169M8/18/108:45AM to 12:30 PM
    9R6799BLBLABXD171F8/17/101:15 PM to 5 PM
    10R6795BLBLABXD185M8/17/101:15 PM to 5 PM
    11R6787BLBLABXD1187F8/17/101:15 PM to 5 PM
    12R6785BLBLABXD1176M8/17/101:15 PM to 5 PM
    13R6819BLBLABXD1278F8/18/108:45AM to 12:30 PM
    14R6789BLBLABXD1273M8/17/101:15 PM to 5 PM
    15R6805BLBLABXD1277M8/17/101:15 PM to 5 PM
    16R6291BLBLABXD13N/AM6/11/09N/A
    17R6811BLBLABXD1481F8/18/108:45AM to 12:30 PM
    18R6825BLBLABXD1481M8/18/108:45AM to 12:30 PM
    19R6657BLBLABXD16N/AM1/8/08N/A
    20R6054BLBLABXD19N/AF2/26/08N/A
    21R6052BLBLABXD19N/AM2/26/08N/A
    22R6803BLBLABXD2485F8/17/101:15 PM to 5 PM
    23R6817BLBLABXD2486M8/18/108:45AM to 12:30 PM
    24R6063BLBLABXD25N/AF3/12/08N/A
    25R6062BLBLABXD25N/AM3/12/08N/A
    26R6659BLBLABXD27N/AF1/8/08N/A
    27R6791BLBLABXD2775F8/17/101:15 PM to 5 PM
    28R6797BLBLABXD2971F8/17/101:15 PM to 5 PM
    29R6793BLBLABXD2971M8/17/101:15 PM to 5 PM
    30R6815BLBLABXD3174F8/18/108:45AM to 12:30 PM
    31R6801BLBLABXD3173M8/17/101:15 PM to 5 PM
    32R6915BLBLABXD3281F8/18/101 PM to 6:45 PM
    33R6845BLBLABXD3281M8/18/108:45AM to 12:30 PM
    34R6821BLBLABXD3477F8/18/108:45AM to 12:30 PM
    35R6807BLBLABXD3477M8/18/108:45AM to 12:30 PM
    36R6057BLBLABXD38N/AF2/26/08N/A
    37R6056BLBLABXD38N/AM2/26/08N/A
    38R6827BLBLABXD3979F8/18/108:45AM to 12:30 PM
    39R6813BLBLABXD3979M8/18/108:45AM to 12:30 PM
    40R6847BLBLABXD4085F8/18/108:45AM to 12:30 PM
    41R6849BLBLABXD4085M8/18/108:45AM to 12:30 PM
    42R6809BLBLABXD4287F8/18/108:45AM to 12:30 PM
    43R6823BLBLABXD4287M8/18/108:45AM to 12:30 PM
    44R6759BLBLABXD4381F8/17/109:30 AM to 12:30AM
    45R6757BLBLABXD4381M8/17/109:30 AM to 12:30AM
    46R6745BLBLABXD4483F8/17/109:30 AM to 12:30AM
    47R6763BLBLABXD4577F8/17/109:30 AM to 12:30AM
    48R6761BLBLABXD4577M8/17/109:30 AM to 12:30AM
    49R6879BLBLABXD4876F8/18/101 PM to 6:45 PM
    50R6881BLBLABXD4876M8/18/101 PM to 6:45 PM
    51R6751BLBLABXD4984F8/17/109:30 AM to 12:30AM
    52R6747BLBLABXD4984M8/17/109:30 AM to 12:30AM
    53R6104BLBLABXD5N/Af10/23/09N/A
    54R6103BLBLABXD5N/AM10/23/09N/A
    55R6889BLBLABXD5077F8/18/101 PM to 6:45 PM
    56R6891BLBLABXD5077M8/18/101 PM to 6:45 PM
    57R6074BLBLABXD51N/AF3/12/08N/A
    58R6699BLBLABXD51N/AM4/30/09N/A
    59R6917BLBLABXD5684F8/18/101 PM to 6:45 PM
    60R6893BLBLABXD5677M8/18/101 PM to 6:45 PM
    61R6769BLBLABXD6070F8/17/109:30 AM to 12:30AM
    62R6771BLBLABXD6070M8/17/101:15 PM to 5 PM
    63R6655BLBLABXD61N/AF1/29/08N/A
    64R6653BLBLABXD61N/AM1/29/08N/A
    65R6835BLBLABXD6283F8/18/108:45AM to 12:30 PM
    66R6843BLBLABXD6283M8/18/108:45AM to 12:30 PM
    67R6887BLBLABXD6377F8/18/101 PM to 6:45 PM
    68R6885BLBLABXD6377M8/18/101 PM to 6:45 PM
    69R6877BLBLABXD6584F8/18/101 PM to 6:45 PM
    70R6873BLBLABXD6584M8/18/101 PM to 6:45 PM
    71R6929BLBLABXD6876F8/18/101 PM to 6:45 PM
    72R6931BLBLABXD6876M8/18/101 PM to 6:45 PM
    73R6775BLBLABXD6969F8/17/101:15 PM to 5 PM
    74R6773BLBLABXD6980M8/17/101:15 PM to 5 PM
    75R6925BLBLABXD7076F8/18/101 PM to 6:45 PM
    76R6921BLBLABXD7076M8/17/061 PM to 6:45 PM
    77R6869BLBLABXD7176F8/18/101 PM to 6:45 PM
    78R6871BLBLABXD7176M8/18/101 PM to 6:45 PM
    79R6777BLBLABXD7383F8/17/101:15 PM to 5 PM
    80R6779BLBLABXD7383M8/17/101:15 PM to 5 PM
    81R6837BLBLABXD7576F8/18/108:45AM to 12:30 PM
    82R6829BLBLABXD7576M8/18/108:45AM to 12:30 PM
    83R6933BLBLABXD7987F8/18/101 PM to 6:45 PM
    84R6935BLBLABXD7987M8/18/101 PM to 6:45 PM
    85R6781BLBLABXD8073F8/17/101:15 PM to 5 PM
    86R6783BLBLABXD8073M8/17/101:15 PM to 5 PM
    87R6913BLBLABXD8381F8/18/101 PM to 6:45 PM
    88R6911BLBLABXD8381M8/18/101 PM to 6:45 PM
    89R6841BLBLABXD8476F8/18/108:45AM to 12:30 PM
    90R6833BLBLABXD8476M8/18/108:45AM to 12:30 PM
    91R6937BLBLABXD8574F8/18/101 PM to 6:45 PM
    92R6939BLBLABXD8574M8/18/101 PM to 6:45 PM
    93R6909BLBLABXD8783F8/18/101 PM to 6:45 PM
    94R6895BLBLABXD8982F8/18/101 PM to 6:45 PM
    95R6897BLBLABXD8982M8/18/101 PM to 6:45 PM
    96R6903BLBLABXD9082F8/18/101 PM to 6:45 PM
    97R6905BLBLABXD9082M8/18/101 PM to 6:45 PM
    98R6923BLBLABXD9286F8/18/101 PM to 6:45 PM
    99R6927BLBLABXD9289M8/18/101 PM to 6:45 PM
    100R6919BLBLABXD9576F8/18/101 PM to 6:45 PM
    101R6867BLBLABXD9576M8/18/108:45AM to 12:30 PM
    102R6899BLBLABXD9771F8/18/101 PM to 6:45 PM
    103R6901BLBLABXD9771M8/18/101 PM to 6:45 PM
    104R6875BLBLABXD9977F8/18/101 PM to 6:45 PM
    105R6883BLBLABXD9977M8/18/101 PM to 6:45 PM
    106R6831BLBLABXD10083M8/18/108:45AM to 12:30 PM
    107R6943BLBLABXD10189F8/18/101 PM to 6:45 PM
    108R6941BLBLABXD10189M8/18/101 PM to 6:45 PM
    109R6753BLBLABXD10288F8/17/109:30 AM to 12:30AM
    110R6755BLBLABXD10288M8/17/109:30 AM to 12:30AM
    111R6765BLBLABXD10378M8/17/109:30 AM to 12:30AM
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diff --git a/general/datasets/INIA_AmgCoh_0311/platform.rtf b/general/datasets/INIA_AmgCoh_0311/platform.rtf new file mode 100644 index 0000000..aba2206 --- /dev/null +++ b/general/datasets/INIA_AmgCoh_0311/platform.rtf @@ -0,0 +1 @@ +

[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)

diff --git a/general/datasets/INIA_AmgCoh_0311/processing.rtf b/general/datasets/INIA_AmgCoh_0311/processing.rtf new file mode 100644 index 0000000..a2a6c30 --- /dev/null +++ b/general/datasets/INIA_AmgCoh_0311/processing.rtf @@ -0,0 +1,16 @@ +

Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.

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Batch Effects. This data set required no initial correction for batch effects and the data in this initial release do not incorporate any additional corrections. However, there are several confounder-like factors that should be considered:

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  1. Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
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  2. Dissection variation: examine and use probe sets for Ttr as a correction for the inclusion of choroid plexus and non-parenchmymal tissue in samples. Transthyretin is only expressed in the choroid plexus (PMID 16698124
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  3. Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the 54 probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases (58) in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest 54 probe sets in this amygdala data set accounts of 42% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the amygdala data set can be map as a trait. It is not associated with any QLTs that are even suggestive, and the highest LRS is about 10 on chromosomes 18 and 19. The second principal component trait, which accounts for only 5% of the "noise" variance, has a suggestive QTL (LRS of 12, high B allele) on chromosome 4 at about 90 Mb. We therefore do not think that there is significant risk of major false trans eQTL bands in this data set.
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Data Release. This data set was first uploaded into GeneNetwork November 25, 2010 and made accessible without a password to all users on December 1, 2010. The data set was orginally entered with two strain identification errors that were fixed Dec 10, 2010 by KM Mozhui and A Centeno (array R6659BL was originally listed as BXD16 but is BXD27; R6789BL was original listed as BXD27 is BXD12). The current data release has no known errors of sex or strain assignment.

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Data Status and Use. The data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
+This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.

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Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.

diff --git a/general/datasets/INIA_AmgCoh_0311/summary.rtf b/general/datasets/INIA_AmgCoh_0311/summary.rtf new file mode 100644 index 0000000..41311b7 --- /dev/null +++ b/general/datasets/INIA_AmgCoh_0311/summary.rtf @@ -0,0 +1 @@ +

This is a final error-checked release of an amygdala gene expression data set generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from the NIH NIAAA. The basolateral complex of the amygdala of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").

diff --git a/general/datasets/INIA_AmgCoh_0311/tissue.rtf b/general/datasets/INIA_AmgCoh_0311/tissue.rtf new file mode 100644 index 0000000..ea556c7 --- /dev/null +++ b/general/datasets/INIA_AmgCoh_0311/tissue.rtf @@ -0,0 +1,12 @@ +

Dissection Protocol

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  1. Animals were sacrificed by cervical dislocation and brains were immediately dissected from the head and stored in RNAlater (www.ambion.com) for 2 to 3 days at 4 deg C in a refrigerator.
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  2. Brains were placed with ventral side up on a cutting surface and a partial coronal cut was made with a surgical blade at a level that corresponds approximately to the -2.5 mm behind the stereotaxic Bregma point (this cut is just a little rostral from the pontine fibres when viewed from the ventral side).
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  3. Brains were placed in a coronal matrix (egg-style slicer) and a 2-mm thick coronal slab was taken just rostral to the initial cut.
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  4. The 2-mm thick slab was placed on a clean glass slide and the hypothalamus was cut out and placed in a tube on dry ice.
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  5. To dissect the BLA, the temporal lobes were detached by placing a scalpel in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then cut out and placed in a tube on dry ice.
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  6. Tissue from two mice (right and left sides) and from the same strain and sex (an usually the same litter) were pooled. The only exceptions are BLA samples from strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue was obtained from only one animal per array).
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