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
Pancreas
GSM2136955 GSM2136956 GSM2136963 GSM2136964 GSM2136971 GSM2136972
GSM2136959 GSM2136960 GSM2136967 GSM2136968 GSM2136975 GSM2136976
GSM2136957 GSM2136958 GSM2136965 GSM2136966 GSM2136973 GSM2136974
GSM2136961 GSM2136962 GSM2136969 GSM2136970 GSM2136977 GSM2136978
Description

Submission Date: Apr 28, 2016

Summary: The transcriptomes of four subpopulations of beta cells isolated by FACS from five healthy human donors. Populations were defined using cell surface-labeling antibodies, avoiding the need for fixation.

GEO Accession ID: GSE80780

PMID: 27399229

Description

Submission Date: Apr 28, 2016

Summary: The transcriptomes of four subpopulations of beta cells isolated by FACS from five healthy human donors. Populations were defined using cell surface-labeling antibodies, avoiding the need for fixation.

GEO Accession ID: GSE80780

PMID: 27399229

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.