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
Islets
GSM2705881 GSM2705884 GSM2705885
GSM2705886 GSM2705887 GSM2705891
GSM2705880 GSM2705882 GSM2705883 GSM2705889 GSM2705892 GSM2705893
GSM2705888 GSM2705890 GSM2705894
Description

Submission Date: Jul 17, 2017

Summary: We have performed RNA-seq on mouse islets lacking all p300 (p300 KO), all CBP (CBP-null), and one copy of CBP and all p300 (triallelic). The data revealed that p300 and CBP regulate some distinct but largely overlapping genes in islets. This was further confirmed by GO term and transcription factor target analyses, which suggested that these coactivators regulate genes that function similarly and converge to Hnf1a pathway.

GEO Accession ID: GSE101537

PMID: 29217654

Description

Submission Date: Jul 17, 2017

Summary: We have performed RNA-seq on mouse islets lacking all p300 (p300 KO), all CBP (CBP-null), and one copy of CBP and all p300 (triallelic). The data revealed that p300 and CBP regulate some distinct but largely overlapping genes in islets. This was further confirmed by GO term and transcription factor target analyses, which suggested that these coactivators regulate genes that function similarly and converge to Hnf1a pathway.

GEO Accession ID: GSE101537

PMID: 29217654

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.