GenePy

GenePy calculates gene-level pathogenicity scores from next-generation sequencing (NGS) variant data to quantify cumulative genetic burden per gene and support analysis of complex, multifactorial disease genetics.

Key Features:

• Gene-Level Scoring System: Calculates per-individual gene- and pathway-level scores that reflect cumulative pathogenic burden derived from NGS variants.
• Incorporation of Multiple Metrics: Integrates population allele frequency estimates, individual zygosity determined through standard variant calling pipelines, and user-defined deleteriousness metrics into the scoring.
• Integration and Flexibility: Produces scores suitable for incorporation into machine learning, network analysis, and topological approaches.
• Correction for Gene Length: Applies gene-length correction to per-gene scores to enable meaningful comparisons across genes.
• Performance Evaluation: Demonstrated on whole-exome sequencing data from 508 individuals, where GenePy distinguished positive control genes with Mann-Whitney U test p = 1.37 × 10^-4 versus p = 0.003 for a commonly applied association tool.
• Data Integration: Outputs per-gene scores compatible with downstream integration with transcriptomic and proteomic datasets.

Scientific Applications:

• Complex disease genetics: Quantifying individual genetic burden and assessing gene-level contributions in common multifactorial diseases.
• Multi-omics integration: Enabling integration of gene-level genomic scores with transcriptomic and proteomic data for comprehensive multi-omics studies.

Methodology:

Aggregates per-sample NGS variant data, incorporates population allele frequency, individual zygosity from standard variant calling pipelines and user-defined deleteriousness metrics, applies gene-length correction to produce per-gene scores, and evaluates significance using Mann-Whitney U tests as reported.