GSE133903: Transcriptome analyses of human pancreatic islets and pseudoislets

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
Human pancreatic islets
GSM3929502 GSM3929503 GSM3929504 GSM3929505
GSM3929497 GSM3929498 GSM3929499 GSM3929500 GSM3929501
Description

Submission Date: Jul 06, 2019

Summary: We have observed an improvement of glucose-stimulated insulin secretion upon the formation of pseudoislets. Transcriptome analyses of islets and pseudoislets from the same human donor were performed to determine the functional improvement. We identified 38844 transcripts and revealed that unlike islets, pseudoislets were deprived of exocrine and endothelial cells. In addition, the mRNA levels of proteins related to apoptosis and inflammation as well as the components of extracellular matrix were less abundant in pseudoislets.

GEO Accession ID: GSE133903

PMID: 31311971

Description

Submission Date: Jul 06, 2019

Summary: We have observed an improvement of glucose-stimulated insulin secretion upon the formation of pseudoislets. Transcriptome analyses of islets and pseudoislets from the same human donor were performed to determine the functional improvement. We identified 38844 transcripts and revealed that unlike islets, pseudoislets were deprived of exocrine and endothelial cells. In addition, the mRNA levels of proteins related to apoptosis and inflammation as well as the components of extracellular matrix were less abundant in pseudoislets.

GEO Accession ID: GSE133903

PMID: 31311971

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.