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 |
|---|---|---|
| Human islet graft |
GSM4157059 GSM4157065 GSM4157060 GSM4157061
|
|
|
GSM4157054 GSM4157055 GSM4157056 GSM4157057 GSM4157058
|
||
|
GSM4157062 GSM4157066 GSM4157063 GSM4157064
|
Submission Date: Nov 12, 2019
Summary: We used RNA-seq to investigate transcriptional changes in human islet grafts that were treated in vivo with tacrolimus or sirolimus. We show that this treatment induces broad transcriptional dysregulation related to peptide processing, ion/calcium flux, and the extracellular matrix.
GEO Accession ID: GSE140230
PMID: 31941840
Submission Date: Nov 12, 2019
Summary: We used RNA-seq to investigate transcriptional changes in human islet grafts that were treated in vivo with tacrolimus or sirolimus. We show that this treatment induces broad transcriptional dysregulation related to peptide processing, ion/calcium flux, and the extracellular matrix.
GEO Accession ID: GSE140230
PMID: 31941840
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.