VarSAn

VarSAn identifies biological pathways associated with sets of genomic variants through network-based analysis to interpret variant impacts on disease and drug response.

Key Features:

• Network Analysis Algorithm: Implements a Random Walk with Restarts (RWR) on a configurable network of nodes representing genomic variants, genes, and biological pathways to rank pathway relevance.
• Pathway Relevance Ranking: Assigns P-values to pathways to quantify statistical relevance to the input variant set.
• Distinct Treatment of Variants: Differentiates non-coding and coding variants and accounts for the number of pathways each variant affects.
• Identification Beyond Direct Gene Impact: Detects relevant pathways even when many variants do not directly impact genes within those pathways.

Scientific Applications:

• Disease Association: Identifies pathways relevant to genomic variants associated with cancer and other diseases.
• Drug Response Variation: Relates genetic variation to differences in drug response for applications in personalized medicine.
• Complementary Pathway Ranking: Provides pathway rankings that complement traditional gene-set enrichment tests on genes related to query sets.
• Benchmarking Strategy: Has been evaluated using a benchmarking strategy to quantify advantages over standard methods.
• Discovery of Key Pathways: Applied to de novo variants in Hypoplastic Left Heart Syndrome to identify pathways such as the VEGFA-VEGFR2 pathway.

Methodology:

Applies Random Walk with Restarts (RWR) on a configurable network of variants, genes, and pathways to rank pathways and assign P-values, distinguishes non-coding versus coding variants, accounts for the number of pathways affected per variant, and identifies pathways even without direct gene-variant overlaps.