Pathway-PDT

Pathway-PDT performs pathway-level association analysis of family-based GWAS data using the PDT framework to detect significant gene sets in general nuclear families.

Key Features:

• Framework Utilization: Pathway-PDT employs the PDT framework to analyze raw genotypic data from general nuclear families, including datasets with multiple siblings and missing parental information.
• Analytical Power: Simulation studies show Pathway-PDT has greater power than p-value based methods such as ALIGATOR and the PLINK set-based test when applied to general nuclear families.
• Computational Implementation: Pathway-PDT is implemented in C++ using POSIX threads to enable efficient processing of large-scale family GWAS datasets.

Scientific Applications:

• Family-based pathway analysis: Detects pathway-level associations in family-based GWAS by leveraging familial genotype information.
• Genetic epidemiology of heritable traits: Supports studies aiming to uncover genetic interactions and pathways contributing to heritable traits or diseases.
• Method comparison and power assessment: Facilitates evaluation of pathway-detection power relative to methods like ALIGATOR and PLINK in simulation studies.

Methodology:

Implements the PDT framework on raw genotypic data from general nuclear families (including multiple siblings and missing parents), evaluated via simulation studies against ALIGATOR and the PLINK set-based test, and implemented in C++ with POSIX threads.