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Data Set Group: Hippocampus Mouse Transcriptome Assay 1.0 GeneLevel Main (Nov15) RMA
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Contact Information |
Megan Mulligan
University of Tennessee Health Science Center
855 Monroe Ave Suite 515
Memphis, Tennessee 38163 United States
Tel. 5126802386
mmulliga@uthsc.edu
Website
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Download datasets and supplementary data files |
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Specifics of this Data Set: |
None
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Summary: |
This data set was generated to study the effects of strain and stress on hippocampal gene expression in female mice. The data set includes three inbred strains of mice and four treatment groups.
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About the cases used to generate this set of data: |
The original data set included four individuals of each strain under baseline (B) conditions and eight individuals from each strain for each of the treatment groups, chronic mild stress (C), acute restraint (R), and chronic mild stress followed by acute retraint (CR). However, some samples have been removed due to technical problems with tissue collection or microarray performance.
MTA_ID |
MTA prefix |
GN_ID |
FM_ID |
Mouse_ID |
CaseId |
Strain |
Strain_Code |
Treatment code |
NanoDrop, ng/ul |
NanoDrop, 260/280 |
NanoDrop, 260/230 |
Agilent, ng/µl |
RIN |
Notes |
1 |
BCJ 1.CMS_ |
D-B-215-1 |
CMS_000215 |
215 |
020615.01 |
DBA/2J |
D |
B |
163.61 |
1.9 |
2.31 |
130 |
8.6 |
|
2 |
BCJ 2.CMS_ |
D-C-86-1 |
CMS_000086 |
86 |
012115.23 |
DBA/2J |
D |
C |
98.51 |
1.79 |
2.4 |
329 |
8.8 |
|
3 |
BCJ 3.CMS_ |
D-CR-94-1 |
CMS_000094 |
94 |
012115.16 |
DBA/2J |
D |
CR |
162.78 |
1.87 |
2.38 |
166 |
9.2 |
|
4 |
BCJ 4.CMS_ |
D-R-133-1 |
CMS_000133 |
133 |
012115.14 |
DBA/2J |
D |
R |
88.95 |
1.82 |
2.45 |
90 |
8.2 |
|
5 |
BCJ 5.CMS_ |
B-B-208-1 |
CMS_000208 |
208 |
012215.04 |
C57BL/6J |
B |
B |
129.24 |
1.86 |
2.41 |
223 |
8.1 |
|
6 |
BCJ 6.CMS_ |
B-C-101-1 |
CMS_000101 |
101 |
012115.25 |
C57BL/6J |
B |
C |
72.29 |
1.86 |
2.26 |
135 |
9.2 |
|
7 |
BCJ 7.CMS_ |
B-CR-109-1 |
CMS_000109 |
109 |
012115.21 |
C57BL/6J |
B |
CR |
158.56 |
1.7 |
2.46 |
305 |
8.8 |
Microarray outlier; sample removed. |
8 |
BCJ 8.CMS_ |
B-R-143-1 |
CMS_000143 |
143 |
012215.08 |
C57BL/6J |
B |
R |
161.57 |
1.86 |
2.38 |
217 |
9.3 |
|
9 |
BCJ 9.CMS_ |
N-B-210-1 |
CMS_000210 |
210 |
012115.04 |
C57BL/6NJ |
N |
B |
132.39 |
1.89 |
2.3 |
192 |
8.5 |
|
10 |
BCJ 10.CMS_ |
N-C-117-1 |
CMS_000117 |
117 |
012115.30 |
C57BL/6NJ |
N |
C |
151.43 |
1.91 |
2.38 |
187 |
8.8 |
|
11 |
BCJ 11.CMS_ |
N-CR-126-1 |
CMS_000126 |
126 |
012115.33 |
C57BL/6NJ |
N |
CR |
137.87 |
1.88 |
2.29 |
76 |
9 |
|
12 |
BCJ 12.CMS_ |
N-R-152-1 |
CMS_000152 |
152 |
012215.29 |
C57BL/6NJ |
N |
R |
197.95 |
1.88 |
2.35 |
150 |
9.1 |
|
13 |
BCJ 13.CMS_ |
D-B-216-1 |
CMS_000216 |
216 |
020615.02 |
DBA/2J |
D |
B |
98.64 |
1.91 |
2.03 |
60 |
8.6 |
|
15 |
BCJ 15.CMS_ |
D-CR-93-1 |
CMS_000093 |
93 |
012115.11 |
DBA/2J |
D |
CR |
71.36 |
1.83 |
2.25 |
109 |
8.5 |
|
16 |
BCJ 16.CMS_ |
D-R-134-1 |
CMS_000134 |
134 |
012115.17 |
DBA/2J |
D |
R |
73.49 |
1.85 |
2.43 |
149 |
8.2 |
|
17 |
BCJ 17.CMS_ |
B-B-205-1 |
CMS_000205 |
205 |
012015.02 |
C57BL/6J |
B |
B |
174.78 |
2.02 |
2.21 |
266 |
8.9 |
|
18 |
BCJ 18.CMS_ |
B-C-104-1 |
CMS_000104 |
104 |
012215.30 |
C57BL/6J |
B |
C |
84.7 |
2.64 |
2.01 |
168 |
9.2 |
|
19 |
BCJ 19.CMS_ |
B-CR-110-1 |
CMS_000110 |
110 |
012115.26 |
C57BL/6J |
B |
CR |
136.7 |
1.96 |
2.16 |
178 |
9.5 |
|
20 |
BCJ 20.CMS_ |
B-R-141-1 |
CMS_000141 |
141 |
012115.22 |
C57BL/6J |
B |
R |
86.04 |
20.2 |
2.53 |
208 |
8.9 |
|
21 |
BCJ 21.CMS_ |
N-B-209-1 |
CMS_000209 |
209 |
012015.04 |
C57BL/6NJ |
N |
B |
98.3 |
1.99 |
2.35 |
169 |
8.8 |
|
22 |
BCJ 22.CMS_ |
N-C-119-1 |
CMS_000119 |
119 |
012215.18 |
C57BL/6NJ |
N |
C |
94.63 |
1.96 |
2.36 |
179 |
8.5 |
|
24 |
BCJ 24.CMS_ |
N-R-150-1 |
CMS_000150 |
150 |
012115.29 |
C57BL/6NJ |
N |
R |
407.34 |
1.98 |
2.24 |
425 |
7.5 |
Microarray outlier; sample removed. |
25 |
BCJ 25.CMS_ |
D-B-217-1 |
CMS_000217 |
217 |
020615.03 |
DBA/2J |
D |
B |
84.61 |
1.82 |
2.18 |
177 |
7.9 |
|
26 |
BCJ 26.CMS_ |
D-C-85-1 |
CMS_000085 |
85 |
012115.20 |
DBA/2J |
D |
C |
172.86 |
1.98 |
2.27 |
288 |
8.9 |
|
27 |
BCJ 27.CMS_ |
D-CR-95-1 |
CMS_000095 |
95 |
012215.16 |
DBA/2J |
D |
CR |
109.8 |
1.98 |
2.47 |
157 |
8.9 |
|
28 |
BCJ 28.CMS_ |
D-R-132-1 |
CMS_000132 |
132 |
012015.29 |
DBA/2J |
D |
R |
140.82 |
1.91 |
2.47 |
318 |
9 |
|
29 |
BCJ 29.CMS_ |
B-B-207-1 |
CMS_000207 |
207 |
012215.02 |
C57BL/6J |
B |
B |
96.25 |
1.89 |
2.67 |
176 |
8.5 |
|
30 |
BCJ 30.CMS_ |
B-C-102-1 |
CMS_000102 |
102 |
012115.28 |
C57BL/6J |
B |
C |
129.69 |
1.89 |
2.32 |
105 |
8.7 |
|
31 |
BCJ 31.CMS_ |
B-CR-111-1 |
CMS_000111 |
111 |
012215.26 |
C57BL/6J |
B |
CR |
165.67 |
1.84 |
2.31 |
176 |
9.5 |
|
32 |
BCJ 32.CMS_ |
B-R-142-1 |
CMS_000142 |
142 |
012115.24 |
C57BL/6J |
B |
R |
116.93 |
1.84 |
2.22 |
96 |
9.4 |
|
33 |
BCJ 33.CMS_ |
N-B-211-1 |
CMS_000211 |
211 |
012315.02 |
C57BL/6NJ |
N |
B |
106 |
2.09 |
2.29 |
156 |
7.4 |
|
34 |
BCJ 34.CMS_ |
N-C-118-1 |
CMS_000118 |
118 |
012115.32 |
C57BL/6NJ |
N |
C |
219.2 |
1.91 |
2.34 |
197 |
9.2 |
|
35 |
BCJ 35.CMS_ |
N-CR-127-1 |
CMS_000127 |
127 |
012215.33 |
C57BL/6NJ |
N |
CR |
89 |
2 |
2.56 |
157 |
9.4 |
|
36 |
BCJ 36.CMS_ |
N-R-149-1 |
CMS_000149 |
149 |
012115.27 |
C57BL/6NJ |
N |
R |
72.91 |
1.84 |
2.14 |
107 |
8.6 |
|
37 |
BCJ 37.CMS_ |
D-B-218-1 |
CMS_000218 |
218 |
020615.04 |
DBA/2J |
D |
B |
154.34 |
1.99 |
1.99 |
119 |
9.3 |
|
38 |
BCJ 38.CMS_ |
D-C-87-1 |
CMS_000087 |
87 |
012215.13 |
DBA/2J |
D |
C |
105.3 |
1.98 |
2.21 |
109 |
7.4 |
|
39 |
BCJ 39.CMS_ |
D-CR-97-1 |
CMS_000097 |
97 |
012315.05 |
DBA/2J |
D |
CR |
55.85 |
1.89 |
2.41 |
85 |
8.3 |
|
40 |
BCJ 40.CMS_ |
D-R-137-1 |
CMS_000137 |
137 |
012315.06 |
DBA/2J |
D |
R |
128.97 |
2.01 |
2.24 |
159 |
8.1 |
Microarray outlier; sample removed. |
41 |
BCJ 41.CMS_ |
B-B-206-1 |
CMS_000206 |
206 |
012115.02 |
C57BL/6J |
B |
B |
159.89 |
2.03 |
2.1 |
273 |
7.8 |
|
42 |
BCJ 42.CMS_ |
B-C-103-1 |
CMS_000103 |
103 |
012215.15 |
C57BL/6J |
B |
C |
111.79 |
1.87 |
2.45 |
160 |
8.9 |
|
43 |
BCJ 43.CMS_ |
B-CR-112-1 |
CMS_000112 |
112 |
012215.31 |
C57BL/6J |
B |
CR |
172.14 |
1.86 |
2.22 |
180 |
9.4 |
|
44 |
BCJ 44.CMS_ |
B-R-145-1 |
CMS_000145 |
145 |
012315.12 |
C57BL/6J |
B |
R |
103.74 |
2.06 |
2.17 |
99 |
8.9 |
|
45 |
BCJ 45.CMS_ |
N-B-212-1 |
CMS_000212 |
212 |
012315.04 |
C57BL/6NJ |
N |
B |
189.5 |
1.9 |
2.4 |
248 |
8.5 |
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47 |
BCJ 47.CMS_ |
N-CR-128-1 |
CMS_000128 |
128 |
012215.34 |
C57BL/6NJ |
N |
CR |
90.65 |
2.07 |
2.25 |
189 |
9.3 |
|
48 |
BCJ 48.CMS_ |
N-R-154-1 |
CMS_000154 |
154 |
012315.29 |
C57BL/6NJ |
N |
R |
114.73 |
1.94 |
2.34 |
167 |
8.8 |
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49 |
BCJ 49.CMS_ |
D-C-88-1 |
CMS_000088 |
88 |
012215.28 |
DBA/2J |
D |
C |
96 |
1.76 |
2.55 |
158 |
8.5 |
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50 |
BCJ 50.CMS_ |
D-CR-96-1 |
CMS_000096 |
96 |
012215.21 |
DBA/2J |
D |
CR |
133.66 |
1.78 |
2.36 |
203 |
8.3 |
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51 |
BCJ 51.CMS_ |
D-R-138-1 |
CMS_000138 |
138 |
012315.22 |
DBA/2J |
D |
R |
127.13 |
1.76 |
2.24 |
81 |
9.3 |
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52 |
BCJ 52.CMS_ |
B-C-105-1 |
CMS_000105 |
105 |
012315.13 |
C57BL/6J |
B |
C |
203.24 |
1.92 |
2.35 |
310 |
7 |
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53 |
BCJ 53.CMS_ |
B-CR-113-1 |
CMS_000113 |
113 |
012315.09 |
C57BL/6J |
B |
CR |
168.67 |
1.82 |
2.41 |
240 |
9.1 |
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55 |
BCJ 55.CMS_ |
N-C-120-1 |
CMS_000120 |
120 |
012215.32 |
C57BL/6NJ |
N |
C |
73.67 |
1.93 |
2.31 |
371 |
8.4 |
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56 |
BCJ 56.CMS_ |
N-CR-125-1 |
CMS_000125 |
125 |
012115.31 |
C57BL/6NJ |
N |
CR |
121.93 |
1.92 |
2.26 |
73 |
8.3 |
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59 |
BCJ 59.CMS_ |
N-C-122-1 |
CMS_000122 |
122 |
012315.30 |
C57BL/6NJ |
N |
C |
131.74 |
1.85 |
2.42 |
186 |
9.4 |
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60 |
BCJ 60.CMS_ |
D-C-89-1 |
CMS_000089 |
89 |
012315.10 |
DBA/2J |
D |
C |
78 |
1.77 |
2.32 |
74 |
8.9 |
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62 |
BCJ 62.CMS_ |
N-CR-130-1 |
CMS_000130 |
130 |
012315.34 |
C57BL/6NJ |
N |
CR |
100.74 |
1.71 |
2.36 |
113 |
8.8 |
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65 |
BCJ 65.CMS_ |
B-R-144-1 |
CMS_000144 |
144 |
012215.27 |
C57BL/6J |
B |
R |
80.1 |
1.81 |
2.3 |
95 |
8.9 |
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66 |
BCJ 66.CMS_ |
N-R-151-1 |
CMS_000151 |
151 |
012215.12 |
C57BL/6NJ |
N |
R |
80.22 |
1.77 |
2.2 |
116 |
8.6 |
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About the tissue used to generate this set of data: |
This data set includes expression data from mouse hippocampus.
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About the array platform: |
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About data values and data processing: |
Outlier Detection. Samples 7 (J-CR-21), 24 (N-R-29), and 40 (D-R-6) were detected as outliers and have abnormal expression profiles (i.e. they do not cluster with other samples and have abnormal median and quartile ranges after normalization. These samples have been removed from the analysis.
RMA Algorithm. The Robust Multichip Analysis (RMA) algorithm fits a robust linear model at the probe level to minimize the effect of probe-specific affinity differences. This approach: n Increases sensitivity to small changes between experiment and control samples. n Minimizes variance across the dynamic range, but does compress calculated fold change values. RMA consists of three steps: 1. Background adjustment 2. Quantile normalization 3. Summarization This is a multi-chip analysis approach. Therefore, all arrays intended for comparison should be included together in the summarization step. For a more detailed description of the RMA algorithm, see the publication, Exploration, Normalization, and Summaries of High Density Oligonucleotide Array Probe Level Data, Biostatistics, April 2003; Vol. 4; Number 2: 249–264.
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Notes: |
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Experiment Type: |
This data set includes four experimental conditions, B (baseline, untreated), C (chronic mild stress), CR (chronic mild stress followed by acute restraint), and R (acute restraint only).
B = untreated
C = 7 weeks of chronic unpredictable stress
R = 30 minutes of restraint
CR = 7 weeks of chronic unpredictable stress followed by 30 minutes of restraint
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Contributor: |
This data set is part of a collaborative effort between UTHSC investigators Byron Jones, Rob Williams, Megan Mulligan, and Lu Lu and collaborators at I.N.R.A Centre de recherche de Toulouse Terenina, Pierre Mormede and Elena Terenina.
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Citation: |
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Data source acknowledgment: |
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Study Id: |
244
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Web services initiated January, 1994 as Portable Dictionary of the Mouse Genome; June 15, 2001 as WebQTL; and Jan 5, 2005 as GeneNetwork.
This site is currently operated by
Rob Williams,
Pjotr Prins,
Zachary Sloan,
Arthur Centeno. Design and code by Pjotr Prins, Zach Sloan, Arthur Centeno, Danny Arends, Christian Fischer, Sam Ockman, Lei Yan, Xiaodong Zhou, Christian Fernandez, Ning Liu, Rudi Alberts, Elissa Chesler, Sujoy Roy, Evan G. Williams, Alexander G. Williams, Kenneth Manly, Jintao Wang, and Robert W. Williams, colleagues.
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GeneNetwork support from:
- The UT Center for Integrative and Translational Genomics
- NIGMS Systems Genetics and Precision Medicine project (R01 GM123489, 2017-2021)
- NIDA NIDA Core Center of Excellence in Transcriptomics, Systems Genetics,
and the Addictome (P30 DA044223, 2017-2022)
- NIA Translational Systems Genetics of Mitochondria, Metabolism, and Aging (R01AG043930, 2013-2018)
- NIAAA Integrative Neuroscience Initiative on Alcoholism (U01 AA016662, U01 AA013499, U24 AA013513, U01 AA014425, 2006-2017)
- NIDA, NIMH, and NIAAA (P20-DA 21131, 2001-2012)
- NCI MMHCC (U01CA105417), NCRR, BIRN, (U24 RR021760)
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