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
Human islet cells
GSM1893652 GSM1893654 GSM1893658
GSM1893651 GSM1893655 GSM1893657
GSM1893650 GSM1893653 GSM1893656
Description

Submission Date: Sep 25, 2015

Summary: We applied RNA-seq analysis to human islet cells, received from 3 independent donors, treated with either redifferentiation cocktail + ARX shRNA, or redifferentiation cocktail + control shRNA or left untreated.

GEO Accession ID: GSE73433

PMID: 26856418

Description

Submission Date: Sep 25, 2015

Summary: We applied RNA-seq analysis to human islet cells, received from 3 independent donors, treated with either redifferentiation cocktail + ARX shRNA, or redifferentiation cocktail + control shRNA or left untreated.

GEO Accession ID: GSE73433

PMID: 26856418

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:

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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.