TARV

TARV performs tree-based analysis of rare genetic variants to identify associations and gene-gene interactions underlying complex diseases using data from next-generation sequencing (NGS).

Key Features:

• Nonparametric Disease Model: Employs a nonparametric framework to flexibly model complex diseases involving multiple genes and interactions.
• Tree-Based Analysis: Structures variant data hierarchically to explore relationships between rare variants and disease phenotypes.
• Gene-Gene Interaction Exploration: Investigates gene-gene interactions, including non-linear effects, that influence disease risk.
• Comparative Performance: Demonstrated superior performance relative to the sequence kernel association test (SKAT) across various simulation scenarios.

Scientific Applications:

• SAGE cohort analysis — CTNNA2: Identified 43 specific variants in CTNNA2 that increased risk of alcoholism in women (odds ratio 1.94), a finding novel to the Study of Addiction: Genetics and Environment (SAGE) dataset and corroborated by subsequent literature reviews.
• SAGE cohort analysis — CNTNAP2: Identified 97 rare variants in CNTNAP2 that reduced risk of alcoholism in women (odds ratio 0.55), indicating a protective effect in the SAGE dataset.

Methodology:

Analyzes NGS-derived variant data using a nonparametric disease model combined with a tree-based analytical approach.