Gene counts are sourced from ARCHS4, which provides uniform alignment of GEO samples.
You can learn more about ARCHS4 and its pipeline here.
Select conditions below to toggle them from the plot:
| GROUP | CONDITION | SAMPLES |
|---|---|---|
| Skeletal muscle |
GSM6572797 GSM6572798 GSM6572799 GSM6572800 GSM6572801
|
|
|
GSM6572802 GSM6572803 GSM6572804 GSM6572805 GSM6572806 GSM6572807
|
Submission Date: Sep 11, 2022
Summary: To investigate the effect of intraperitoneal myriocin treament on skeletal muscle gene expression in aged mice.
GEO Accession ID: GSE213110
PMID: No Pubmed ID
Submission Date: Sep 11, 2022
Summary: To investigate the effect of intraperitoneal myriocin treament on skeletal muscle gene expression in aged mice.
GEO Accession ID: GSE213110
PMID: No Pubmed ID
Visualizations are precomputed using the Python package scanpy on the top 5000 most variable genes.
Differential expression signatures are automatically computed using the limma R package.
More options for differential expression are available to compute below.
Signatures:
Control Condition
Perturbation Condition
Only conditions with at least 1 replicate are available to select
Differential expression signatures can be computed using DESeq2 or characteristic direction.
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.