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Raw gene Expression data is sourced from GEO, and the appropriate db package for mapping probes to gene symbols was sourced from the Bioconductor AnnotationData packages.
You can read more about microarray data here.
Select conditions below to toggle them from the plot:
| GROUP | CONDITION | SAMPLES |
|---|---|---|
| Kidney |
GSM3408211 GSM3408212 GSM3408213
|
|
|
GSM3408208 GSM3408209 GSM3408210
|
Submission Date: Oct 01, 2018
Summary: Methylmalonic acidemia (MMA) is one of the most common inherited metabolic disorders, due to deficiency of the mitochondrial methylmalonyl ̶ coenzyme A mutase (MUT). How MUT deficiency triggers mitochondrial alterations and cell damage remains unknown, preventing the development of disease-modifying therapies.
To assess the effect of MUT deficiency on gene expression we investigated the transcriptome of in kidney cells derived from healthy controls or patients with MMA who harbor inactivating mutations in MUT. Microarray data indicate that MUT deficiency induces a profound and global change in gene expression that may be in part responsible of cellular alterations observed in patient cells.
GEO Accession ID: GSE120683
PMID: 32080200
Submission Date: Oct 01, 2018
Summary: Methylmalonic acidemia (MMA) is one of the most common inherited metabolic disorders, due to deficiency of the mitochondrial methylmalonyl ̶ coenzyme A mutase (MUT). How MUT deficiency triggers mitochondrial alterations and cell damage remains unknown, preventing the development of disease-modifying therapies.
To assess the effect of MUT deficiency on gene expression we investigated the transcriptome of in kidney cells derived from healthy controls or patients with MMA who harbor inactivating mutations in MUT. Microarray data indicate that MUT deficiency induces a profound and global change in gene expression that may be in part responsible of cellular alterations observed in patient cells.
GEO Accession ID: GSE120683
PMID: 32080200
Visualize Samples
Visualizations are precomputed using the Python package scanpy on the top 5000 most variable genes.
Precomputed Differential Gene Expression
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 expression signatures can be computed using DESeq2 or characteristic direction.