Gene Expression Data Explorer
Info Gene counts are sourced from ARCHS4, which provides uniform alignment of GEO samples. You can learn more about ARCHS4 and its pipeline here.
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GROUP CONDITION SAMPLES
Male C57BL/6J mice; High-Fat Diet; 30 deg C
GSM3633201 GSM3633202 GSM3633203 GSM3633204 GSM3633205 GSM3633206 GSM3633207 GSM3633208
GSM3633193 GSM3633194 GSM3633195 GSM3633196 GSM3633197 GSM3633198 GSM3633199 GSM3633200
GSM3633153 GSM3633154 GSM3633155 GSM3633156 GSM3633157 GSM3633158 GSM3633159 GSM3633160
GSM3633145 GSM3633146 GSM3633147 GSM3633148 GSM3633149 GSM3633150 GSM3633151 GSM3633152
Male C57BL/6J mice; control Diet; 20 deg C
GSM3633169 GSM3633170 GSM3633171 GSM3633172 GSM3633173 GSM3633174 GSM3633175 GSM3633176
GSM3633161 GSM3633162 GSM3633163 GSM3633164 GSM3633165 GSM3633166 GSM3633167 GSM3633168
GSM3633121 GSM3633122 GSM3633123 GSM3633124 GSM3633125 GSM3633126 GSM3633127 GSM3633128
GSM3633114 GSM3633115 GSM3633113 GSM3633116 GSM3633117 GSM3633118 GSM3633119 GSM3633120
Male C57BL/6J mice; control Diet; 30 deg C
GSM3633185 GSM3633186 GSM3633187 GSM3633188 GSM3633189 GSM3633190 GSM3633191 GSM3633192
GSM3633177 GSM3633178 GSM3633179 GSM3633180 GSM3633181 GSM3633182 GSM3633183 GSM3633184
GSM3633137 GSM3633138 GSM3633139 GSM3633140 GSM3633141 GSM3633142 GSM3633143 GSM3633144
GSM3633129 GSM3633130 GSM3633131 GSM3633132 GSM3633133 GSM3633134 GSM3633135 GSM3633136
Description

Submission Date: Feb 27, 2019

Summary: We analyzed transcript abundance in interscapular brown and inguinal white adipose tissue of wildtype and UCP1-KO mice either adpated to 20°C or 30°C and fed a high fat or control diet.

GEO Accession ID: GSE127251

PMID: 31714796

Description

Submission Date: Feb 27, 2019

Summary: We analyzed transcript abundance in interscapular brown and inguinal white adipose tissue of wildtype and UCP1-KO mice either adpated to 20°C or 30°C and fed a high fat or control diet.

GEO Accession ID: GSE127251

PMID: 31714796

Visualize Samples

Info Visualizations are precomputed using the Python package scanpy on the top 5000 most variable genes.

Precomputed Differential Gene Expression

Info Differential expression signatures are automatically computed using the limma R package. More options for differential expression are available to compute below.

Signatures:

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Control Condition

Perturbation Condition

Only conditions with at least 1 replicate are available to select

Differential Gene Expression Analysis
Info Differential expression signatures can be computed using DESeq2 or characteristic direction.
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Bulk RNA-seq Appyter

This pipeline enables you to analyze and visualize your bulk RNA sequencing datasets with an array of downstream analysis and visualization tools. The pipeline includes: PCA analysis, Clustergrammer interactive heatmap, library size analysis, differential gene expression analysis, enrichment analysis, and L1000 small molecule search.