GSEL

GSEL detects and quantifies enrichment of evolutionary forces within specified genomic regions to assess evolutionary signals in human genomic data.

Key Features:

• Enrichment detection and quantification: Detects and quantifies enrichment of evolutionary forces using sequence-based evolutionary metrics within specified genomic regions.
• Metric compatibility: Integrates with any sequence-based evolutionary metric.
• Empirical null distributions: Generates empirical null distributions matched to allele frequency and linkage disequilibrium structure of the regions.
• Supported input types: Analyzes sets of human genomic regions from genome-wide assays including GWAS, eQTL mapping, and sequencing experiments (*-seq).
• Implementation: Implemented as a Python package.

Scientific Applications:

• GWAS analysis: Assess enrichment of evolutionary signals at variants identified by genome-wide association studies, illustrated with a BMI GWAS.
• eQTL analysis: Evaluate evolutionary enrichment in genomic regions identified by expression quantitative trait loci mapping.
• Sequencing-based assays: Test evolutionary enrichment in regions derived from sequencing experiments (*-seq).
• Polygenic trait analysis: Probe evolutionary dynamics underlying highly polygenic traits such as body mass index (BMI).

Methodology:

Generates empirical null distributions matched for allele frequency and linkage disequilibrium structure and integrates sequence-based evolutionary metrics to test for enrichment.