Sigma-1 and Sigma-2 Receptor Co-expression Networks Across Five Human Brain Regions

Drake H. Harbert published a transcriptomic analysis comparing sigma-1 (SIGMAR1) and sigma-2 (TMEM97) receptor co-expression architectures. The dataset includes genome-wide Spearman correlation results derived from the GTEx v8 dataset, covering five brain regions with 209 samples in the primary region and 16,225 expressed genes. It was last updated on June 4, 2026.

Use Cases

• Identify gene co-expression partners for SIGMAR1 and TMEM97 based on correlation vectors.
• Compare top co-expression networks between receptors based on the reported binary Jaccard index of 0.100.
• Analyze pathway enrichment for mitochondrial translation and neurodegeneration based on Gene Ontology results.
• Replicate multi-region co-expression patterns across brain regions, including hippocampus-specific convergence.

Strengths

• Analysis is based on the GTEx v8 dataset with 209 samples in the primary region and 16,225 expressed genes.
• Findings were replicated across five brain regions, suggesting methodological consistency.
• Three Weighted Jaccard formulations and cosine similarity were used, with reported high metric robustness (ρ = 0.856).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is small (5.6 KB), indicating limited scope, likely containing summary statistics rather than raw 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.