GSE113764: Transcriptome of human white and brown adipose tissue biopsies

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
BAT
GSM3119100 GSM3119102 GSM3119104 GSM3119106 GSM3119108 GSM3119110
GSM3119113 GSM3119114 GSM3119116 GSM3119118 GSM3119121 GSM3119123 GSM3119124 GSM3119126 GSM3119128
WAT
GSM3119101 GSM3119103 GSM3119105 GSM3119107 GSM3119109 GSM3119111
GSM3119112 GSM3119115 GSM3119117 GSM3119119 GSM3119120 GSM3119122 GSM3119125 GSM3119127 GSM3119129
Description

Submission Date: Apr 27, 2018

Summary: We analyzed coding transcript abundance in paired biopsies of white and brown adipose tissue obtained from the supraclavicular region of 15 healthy subjects.

In a prior experiment measuring 18F-deoxyglucose uptake by PET-CT, 9 subjects displayed active brown fat and 6 did not.

GEO Accession ID: GSE113764

PMID: 29909972

Description

Submission Date: Apr 27, 2018

Summary: We analyzed coding transcript abundance in paired biopsies of white and brown adipose tissue obtained from the supraclavicular region of 15 healthy subjects.

In a prior experiment measuring 18F-deoxyglucose uptake by PET-CT, 9 subjects displayed active brown fat and 6 did not.

GEO Accession ID: GSE113764

PMID: 29909972

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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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.