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.
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GROUP CONDITION SAMPLES
Brown Adipose Tissue
GSM3538042 GSM3538043 GSM3538044 GSM3538045
GSM3538046 GSM3538047 GSM3538048 GSM3538049
Description

Submission Date: Jan 03, 2019

Summary: We describe a role for the poorly annotated protein PGRMC2 in retrograde transport of heme from mitochondria to the nucleus. In absence of PGRMC2, less signaling heme reaches the nucleus, with a consequent alteration of heme-sensitive transcriptional programs that ultimately engenders severe mitochondrial dysfunction in brown adipocytes. These mitochondrial defects compromise, not only the primary function of BAT, to activate thermogenesis and preserve body temperature, but also its contribution to maintain systemic glucose and lipid homeostasis.

GEO Accession ID: GSE124621

PMID: 31748741

Description

Submission Date: Jan 03, 2019

Summary: We describe a role for the poorly annotated protein PGRMC2 in retrograde transport of heme from mitochondria to the nucleus. In absence of PGRMC2, less signaling heme reaches the nucleus, with a consequent alteration of heme-sensitive transcriptional programs that ultimately engenders severe mitochondrial dysfunction in brown adipocytes. These mitochondrial defects compromise, not only the primary function of BAT, to activate thermogenesis and preserve body temperature, but also its contribution to maintain systemic glucose and lipid homeostasis.

GEO Accession ID: GSE124621

PMID: 31748741

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.
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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.