Sigma-1 and Sigma-2 Receptor Co-Expression Networks in Five Human Brain Regions

GTEx v8 data from 209 samples across five brain regions provides genome-wide co-expression analysis for SIGMAR1 and TMEM97 receptors. Drake H. Harbert performed Spearman correlations on 16,225 expressed genes, revealing divergent top networks despite shared global architecture. The dataset, last updated in 2026, includes Weighted Jaccard and Cosine similarity metrics.

Use Cases

• Compare global versus top co-expression network overlap for receptor pairs based on Weighted Jaccard indices
• Identify gene ontology enrichment for mitochondrial translation and neurodegeneration pathways based on SIGMAR1 and TMEM97-specific analyses
• Replicate multi-region co-expression patterns across brain regions based on the GTEx dataset
• Assess the functional divergence of pharmacologically co-classified receptors based on transcriptomic architecture

Strengths

• Analysis includes 209 samples from the GTEx v8 dataset, providing a substantial sample size for brain region comparisons
• Uses genome-wide co-expression data on 16,225 expressed genes, offering broad transcriptomic coverage
• Replicates findings across five distinct brain regions, including the hippocampus, enhancing robustness
• Provides specific similarity metrics (e.g., Weighted Jaccard shifted = 0.964) and p-values (p = 7.5 × 10⁻⁷) for methodological transparency

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download
• The 8.4 KB file size suggests a very limited scope, likely containing summary results rather than raw expression data

Provenance

Source

GTEx v8 dataset

Collection Method

Genome-wide co-expression analysis using Spearman correlations across five brain regions

Freshness

Last updated 2026-06-04 05:40:31; freshness should be verified