PathScore

PathScore quantifies the enrichment of somatic mutations within curated biological pathways across patient datasets to identify pathways recurrently altered in cancer genomics.

Key Features:

• Enrichment Quantification: Calculates the level of enrichment of somatic mutations in predefined pathways to identify biologically significant alterations.
• Cross-Patient Enrichment Detection: Detects pathways that are consistently enriched across multiple patients.
• Effect Size Comparison: Compares pathway effect sizes across samples or cohorts to contextualize the magnitude of enrichment.
• Significance Assessment: Computes significance levels for pathway enrichment to support statistical interpretation.
• Gene-Set Overlap Analysis: Analyzes overlap among gene sets within and between pathways.
• Enrichment Comparison Across Projects: Evaluates differences in pathway enrichment between projects or studies.

Scientific Applications:

• Cancer pathway discovery: Identifies pathways recurrently altered across patient samples to inform studies of tumorigenesis.
• Therapeutic target nomination: Highlights enriched pathways that may indicate candidate therapeutic targets.
• Meta-analysis and cross-study comparison: Enables comparison of pathway enrichment across studies for large-scale genomic investigations.

Methodology:

Uses a statistical approach to determine significance of somatic mutation enrichment within pathways, leverages curated pathway databases, and is implemented in Python with MySQL for data handling.