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 |
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| heart |
GSM5264390 GSM5264392 GSM5264394 GSM5264395
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GSM5264385 GSM5264387 GSM5264388 GSM5264389 GSM5264391
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GSM5264386 GSM5264393 GSM5264396 GSM5264397
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Submission Date: Apr 25, 2021
Summary: Mitochondrial fatty acid oxidation (FAO) is an important energy provider for cardiac work and changes in cardiac substrate preference are associated with different heart diseases. Carnitine palmitoyltransferase 1B (CPT1B) is thought to perform the rate limiting enzyme step in FAO and is inhibited by malonyl-CoA. The role of CPT1B in cardiac metabolism has been addressed by inhibiting or decreasing CPT1B protein or after modulation of tissue malonyl-CoA metabolism. We assessed the role of CPT1B malonyl-CoA sensitivity in cardiac metabolism.
GEO Accession ID: GSE173256
PMID: 29635338
Submission Date: Apr 25, 2021
Summary: Mitochondrial fatty acid oxidation (FAO) is an important energy provider for cardiac work and changes in cardiac substrate preference are associated with different heart diseases. Carnitine palmitoyltransferase 1B (CPT1B) is thought to perform the rate limiting enzyme step in FAO and is inhibited by malonyl-CoA. The role of CPT1B in cardiac metabolism has been addressed by inhibiting or decreasing CPT1B protein or after modulation of tissue malonyl-CoA metabolism. We assessed the role of CPT1B malonyl-CoA sensitivity in cardiac metabolism.
GEO Accession ID: GSE173256
PMID: 29635338
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.