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 |
|---|---|---|
| FACS-enriched β-cells |
GSM2249803 GSM2249804 GSM2249805 GSM2249806 GSM2249807 GSM2249808 GSM2249809 GSM2249810
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GSM2249798 GSM2249799 GSM2249800 GSM2249801 GSM2249802
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GSM2249811 GSM2249812 GSM2249813 GSM2249814 GSM2249815
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Submission Date: Jul 24, 2016
Summary: Utilize high-throughput transcriptomic and cistromic analysis to determine the functional requirement for LDB1 and ISL1 in mature murine pancreatic β-cells while simultaneously assessing their functional interdependence at the chromatin level.
GEO Accession ID: GSE84759
PMID: 27941246
Submission Date: Jul 24, 2016
Summary: Utilize high-throughput transcriptomic and cistromic analysis to determine the functional requirement for LDB1 and ISL1 in mature murine pancreatic β-cells while simultaneously assessing their functional interdependence at the chromatin level.
GEO Accession ID: GSE84759
PMID: 27941246
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.