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
obese male
GSM5381650 GSM5381651 GSM5381652 GSM5381653 GSM5381654 GSM5381655 GSM5381656 GSM5381657 GSM5381658 GSM5381659 GSM5381660 GSM5381661
GSM5381662 GSM5381663 GSM5381664 GSM5381665 GSM5381666 GSM5381667 GSM5381668 GSM5381669 GSM5381670 GSM5381671 GSM5381672 GSM5381673
GSM5381686 GSM5381687 GSM5381688 GSM5381689 GSM5381690 GSM5381691 GSM5381692 GSM5381693 GSM5381694 GSM5381695 GSM5381696 GSM5381697
GSM5381638 GSM5381639 GSM5381640 GSM5381641 GSM5381642 GSM5381643 GSM5381644 GSM5381645 GSM5381646 GSM5381647 GSM5381648 GSM5381649
GSM5381626 GSM5381627 GSM5381628 GSM5381629 GSM5381630 GSM5381631 GSM5381632 GSM5381633 GSM5381634 GSM5381635 GSM5381636 GSM5381637
GSM5381674 GSM5381675 GSM5381676 GSM5381677 GSM5381678 GSM5381679 GSM5381680 GSM5381681 GSM5381682 GSM5381683 GSM5381684 GSM5381685
GSM5159118 GSM5159119 GSM5159120 GSM5159121 GSM5159122 GSM5159123 GSM5159124 GSM5159125 GSM5159126 GSM5159127 GSM5159128 GSM5159129
GSM5159106 GSM5159107 GSM5159108 GSM5159109 GSM5159110 GSM5159111 GSM5159112 GSM5159113 GSM5159114 GSM5159115 GSM5159116 GSM5159117
Description

Submission Date: Mar 11, 2021

Summary: Time restricted eating (TRE) is a simple intervention that has beneficial effects on glucose control in individuals with obesity, who are at high risk of metabolic diseases. TRE altered transcriptomic profile of adipose tissue but series sampling studies are need to evaluate the diurnal changes of gene expression.

GEO Accession ID: GSE168705

PMID: 35912794

Description

Submission Date: Mar 11, 2021

Summary: Time restricted eating (TRE) is a simple intervention that has beneficial effects on glucose control in individuals with obesity, who are at high risk of metabolic diseases. TRE altered transcriptomic profile of adipose tissue but series sampling studies are need to evaluate the diurnal changes of gene expression.

GEO Accession ID: GSE168705

PMID: 35912794

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:

No precomputed signatures are currently available for this study. You can compute differential gene expression on the fly below:

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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.