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
Chronic myeloid leukemia cells
GSM4676420 GSM4676421 GSM4676422 GSM4676423
GSM4676412 GSM4676413 GSM4676414 GSM4676415
GSM4676416 GSM4676417 GSM4676418 GSM4676419
GSM4676424 GSM4676425 GSM4676426 GSM4676427
GSM4676428 GSM4676429 GSM4676430 GSM4676431
Description

Submission Date: Jul 17, 2020

Summary: Bulk RNA sequencing was performed on a CML derived cell line, which contains an TET-ON inducible system for DUX4 inducible expression (DIE). Due to the unconventional cellular background used for the generation of an inducible FSHD cell line, bulk RNA seq was performed to determine if, and otherwise to what extend, this cellular background inteferes with the transcriptional program DUX4 is known to activate in muscle cells.

GEO Accession ID: GSE154649

PMID: No Pubmed ID

Description

Submission Date: Jul 17, 2020

Summary: Bulk RNA sequencing was performed on a CML derived cell line, which contains an TET-ON inducible system for DUX4 inducible expression (DIE). Due to the unconventional cellular background used for the generation of an inducible FSHD cell line, bulk RNA seq was performed to determine if, and otherwise to what extend, this cellular background inteferes with the transcriptional program DUX4 is known to activate in muscle cells.

GEO Accession ID: GSE154649

PMID: No Pubmed ID

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.
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.