GSE143979: Skeletal muscle regeneration is compromised in advanced diabetic peripheral neuropathy

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.
Enter gene symbol:

Select conditions below to toggle them from the plot:

GROUP CONDITION SAMPLES
Abductor Hallucis Muscle
GSM4277575 GSM4277584 GSM4277586
GSM4277572 GSM4277577
GSM4277583
Medial Gastrconemius Muscle
GSM4277579 GSM4277581 GSM4277582 GSM4277585
GSM4277573 GSM4277574 GSM4277576 GSM4277578 GSM4277580
Description

Submission Date: Jan 21, 2020

Summary: DPN muscle exhibits features of degeneration with attempted regeneration. In the most severely pathological muscle samples, regeneration appears to be stymied and our data suggest that this may be partly due to intrinsic dysfunction of the satellite cell pool in addition to extrinsic structural pathology (e.g. nerve damage).

GEO Accession ID: GSE143979

PMID: 32059624

Description

Submission Date: Jan 21, 2020

Summary: DPN muscle exhibits features of degeneration with attempted regeneration. In the most severely pathological muscle samples, regeneration appears to be stymied and our data suggest that this may be partly due to intrinsic dysfunction of the satellite cell pool in addition to extrinsic structural pathology (e.g. nerve damage).

GEO Accession ID: GSE143979

PMID: 32059624

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:

Select conditions:

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.
Select differential expression analysis method:
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.