From d0911a04958a04042da02a334ccc528dae79cc17 Mon Sep 17 00:00:00 2001 From: zsloan Date: Fri, 27 Mar 2015 20:28:51 +0000 Subject: Removed everything from 'web' directory except genofiles and renamed the directory to 'genotype_files' --- web/dbdoc/JAX_CSB_L_0711.html | 373 ------------------------------------------ 1 file changed, 373 deletions(-) delete mode 100755 web/dbdoc/JAX_CSB_L_0711.html (limited to 'web/dbdoc/JAX_CSB_L_0711.html') diff --git a/web/dbdoc/JAX_CSB_L_0711.html b/web/dbdoc/JAX_CSB_L_0711.html deleted file mode 100755 index a800a1a6..00000000 --- a/web/dbdoc/JAX_CSB_L_0711.html +++ /dev/null @@ -1,373 +0,0 @@ - - - -JAX Liver Affy M430 2.0 (Jul11) MDP - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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JAX Liver Affy M430 2.0 (Jul11) MDPmodify this page

- - Accession number: GN357

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Summary:

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High-fat diets are associated with increased obesity and metabolic disease in mice and humans. Here we used analysis of variance (ANOVA) to scrutinize a microarray data set consisting of 10 inbred strains of mice from both sexes fed atherogenic high-fat and control chow diets. An overall F-test was applied to the 40 unique groups of strain-diet-sex to identify 15,288 genes with altered transcription. Bootstrapping k-means clustering separated these changes into four strain-dependent expression patterns, including two sex-related profiles and two diet-related profiles. Sex-induced effects correspond to secretion (males) or fat and energy metabolism (females), whereas diet-induced changes relate to neurological processes (chow) or immune response (high-fat). The full set of pairwise contrasts for differences between strains within sex (90 different statistical tests) uncovered 32,379 total changes. These differences were unevenly distributed across strains and between sexes, indicating that strain-specific responses to high-fat diet differ between sexes. Correlations between expression levels and 8 obesity-related traits identified 5,274 associations between transcript abundance and measured phenotypic endpoints. From this number, 2,678 genes are positively correlated with total cholesterol levels and associate with immune-related categories while 2,596 genes are negatively correlated with cholesterol and connect to cholesterol synthesis. -Keywords: gene expression analysis, strain comparision, effect of dietary fat, sex-specific effects.

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Overall Design:

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One group of mice was fed an atherogenic high-fat (30% fat) diet containing cholic acid to increase fat uptake and another was fed a low-fat (6% fat) regular chow diet. Males and females from both diets were studied for mouse strains 129S1/SvImJ, A/J, BALB/cJ, C3H/HeJ, C57BL/6J, CAST/EiJ, DBA/2J, I/LnJ, MRL/MpJ-Tnfrsf6lpr/J, NZB/BINJ, PERA/Ei, and SM/J. All strains were sacrificed between 11- and 13 weeks of age except for CAST and PERA, which were harvested after 50 weeks of age. CAST and PERA were subsequently removed from our analysis based on discrepant harvest age, but can be found in our database (see below). Three replicate animals were used for each combination of diet, strain, and sex, resulting in a total of 120 mice surveyed for gene expression.

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IndexSample IDStrain IDHF=high-fat (30% fat)
6C=low-fat (6% fat)
Replicate Animal
1GSM264767129S1/SvImJ6CRep1
2GSM264768129S1/SvImJ6CRep2
3GSM264769129S1/SvImJ6CRep3
4GSM264770129S1/SvImJHFRep1
5GSM264771129S1/SvImJHFRep2
6GSM264772129S1/SvImJHFRep3
7GSM264773129S1/SvImJ6CRep1
8GSM264774129S1/SvImJ6CRep2
9GSM264775129S1/SvImJ6CRep3
10GSM264776129S1/SvImJHFRep1
11GSM264777129S1/SvImJHFRep2
12GSM264778129S1/SvImJHFRep3
13GSM264779A/J6CRep1
14GSM264780A/J6CRep2
15GSM264781A/J6CRep3
16GSM264782A/JHFRep1
17GSM264783A/JHFRep2
18GSM264784A/JHFRep3
19GSM264785A/J6CRep1
20GSM264786A/J6CRep2
21GSM264787A/J6CRep3
22GSM264788A/JHFRep1
23GSM264789A/JHFRep2
24GSM264790A/JHFRep3
25GSM264791C57BL/6J6CRep1
26GSM264792C57BL/6J6CRep2
27GSM264793C57BL/6J6CRep3
28GSM264794C57BL/6JHFRep1
29GSM264795C57BL/6JHFRep2
30GSM264796C57BL/6JHFRep3
31GSM264797C57BL/6J6CRep1
32GSM264798C57BL/6J6CRep2
33GSM264799C57BL/6J6CRep3
34GSM264800C57BL/6JHFRep1
35GSM264801C57BL/6JHFRep2
36GSM264802C57BL/6JHFRep3
37GSM264803BALB/cJ6CRep1
38GSM264804BALB/cJ6CRep2
39GSM264805BALB/cJ6CRep3
40GSM264806BALB/cJHFRep1
41GSM264807BALB/cJHFRep2
42GSM264808BALB/cJHFRep3
43GSM264809BALB/cJ6CRep1
44GSM264810BALB/cJ6CRep2
45GSM264811BALB/cJ6CRep3
46GSM264813BALB/cJHFRep1
47GSM264814BALB/cJHFRep2
48GSM264815BALB/cJHFRep3
49GSM264845C3H/HeJ6CRep1
50GSM264846C3H/HeJ6CRep2
51GSM264847C3H/HeJ6CRep3
52GSM264848C3H/HeJHFRep1
53GSM264849C3H/HeJHFRep2
54GSM264850C3H/HeJHFRep3
55GSM264852C3H/HeJ6CRep1
56GSM264853C3H/HeJ6CRep2
57GSM264855C3H/HeJ6CRep3
58GSM264856C3H/HeJHFRep1
59GSM264857C3H/HeJHFRep2
60GSM264858C3H/HeJHFRep3
61GSM264859CAST/EiJ6CRep1
62GSM264861CAST/EiJ6CRep2
63GSM264862CAST/EiJ6CRep3
64GSM264863CAST/EiJHFRep1
65GSM264864CAST/EiJHFRep2
66GSM264865CAST/EiJHFRep3
67GSM264866CAST/EiJ6CRep1
68GSM264867CAST/EiJ6CRep2
69GSM264868CAST/EiJ6CRep3
70GSM264869CAST/EiJHFRep1
71GSM264870CAST/EiJHFRep2
72GSM264871CAST/EiJHFRep3
73GSM264872DBA/2J6CRep1
74GSM264873DBA/2J6CRep2
75GSM264874DBA/2J6CRep3
76GSM264875DBA/2JHFRep1
77GSM264876DBA/2JHFRep2
78GSM264877DBA/2JHFRep3
79GSM264890DBA/2J6CRep1
80GSM264891DBA/2J6CRep2
81GSM264892DBA/2J6CRep3
82GSM264893DBA/2JHFRep1
83GSM264894DBA/2JHFRep2
84GSM264895DBA/2JHFRep3
85GSM264896I/LnJ6CRep1
86GSM264897I/LnJ6CRep2
87GSM264898I/LnJ6CRep3
88GSM264899I/LnJHFRep1
89GSM264900I/LnJHFRep2
90GSM264901I/LnJHFRep3
91GSM264902I/LnJ6CRep1
92GSM264903I/LnJ6CRep2
93GSM264904I/LnJ6CRep3
94GSM264905I/LnJHFRep1
95GSM264906I/LnJHFRep2
96GSM264907I/LnJHFRep3
97GSM264908MRL/MpJ-Fas/J6CRep1
98GSM264909MRL/MpJ-Fas/J6CRep2
99GSM264910MRL/MpJ-Fas/J6CRep3
100GSM264912MRL/MpJ-Fas/JHFRep1
101GSM264913MRL/MpJ-Fas/JHFRep2
102GSM264914MRL/MpJ-Fas/JHFRep3
103GSM264915MRL/MpJ-Fas/J6CRep1
104GSM264916MRL/MpJ-Fas/J6CRep2
105GSM264917MRL/MpJ-Fas/J6CRep3
106GSM264918MRL/MpJ-Fas/JHFRep1
107GSM264920MRL/MpJ-Fas/JHFRep2
108GSM264921MRL/MpJ-Fas/JHFRep3
109GSM264922NZB/BlNJ6CRep1
110GSM264924NZB/BlNJ6CRep2
111GSM264925NZB/BlNJ6CRep3
112GSM264926NZB/BlNJHFRep1
113GSM264928NZB/BlNJHFRep2
114GSM264929NZB/BlNJHFRep3
115GSM264930NZB/BlNJ6CRep1
116GSM264931NZB/BlNJ6CRep2
117GSM264932NZB/BlNJ6CRep3
118GSM264933NZB/BlNJHFRep1
119GSM264935NZB/BlNJHFRep2
120GSM264936NZB/BlNJHFRep3
121GSM265061PERA/EiJ6CRep1
122GSM265062PERA/EiJ6CRep2
123GSM265063PERA/EiJ6CRep3
124GSM265064PERA/EiJHFRep1
125GSM265065PERA/EiJHFRep2
126GSM265066PERA/EiJHFRep3
127GSM265067PERA/EiJ6CRep1
128GSM265068PERA/EiJ6CRep2
129GSM265069PERA/EiJ6CRep3
130GSM265070PERA/EiJHFRep1
131GSM265071PERA/EiJHFRep2
132GSM265072PERA/EiJHFRep3
133GSM265074SM/J6CRep1
134GSM265075SM/J6CRep2
135GSM265105SM/J6CRep3
136GSM265217SM/JHFRep1
137GSM265248SM/JHFRep2
138GSM265275SM/JHFRep3
139GSM265324SM/J6CRep1
140GSM265331SM/J6CRep2
141GSM265357SM/J6CRep3
142GSM265358SM/JHFRep1
143GSM265359SM/JHFRep2
144GSM265360SM/JHFRep3
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Citations:

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Burgess-Herbert SL, Cox A, Tsaih SW, Paigen B. Practical applications of the bioinformatics toolbox for narrowing quantitative trait loci. Genetics 2008 Dec;180(4):2227-35. PMID: 18845850 -Shockley KR, Witmer D, Burgess-Herbert SL, Paigen B et al. Effects of atherogenic diet on hepatic gene expression across mouse strains. Physiol Genomics 2009 Nov 6;39(3):172-82. PMID: 19671657

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Data Source Acknowledgements:

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Churchill GA, Paigen B, Shockley KR, Witmer D

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