OVPDT

OVPDT performs family-based association analysis on sequencing data by integrating an Ordered Subset algorithm, a Variable Threshold algorithm, and Pedigree Disequilibrium Test (PDT) statistics to detect associations of common and rare genetic variants with complex disease phenotypes.

Key Features:

• Integration of Common and Rare Variants: Simultaneously analyzes common and rare genetic variants within family-based sequencing data to capture their combined effects on complex disease.
• Ordered Subset Algorithm: Selects a subset of common variants based on relative risks calculated using parental mating types and prioritizes variants with higher relative risk.
• Variable Threshold Algorithm: Searches for an optimal allele frequency threshold and designates variants below that threshold as candidate rare causal variants.
• Pedigree Disequilibrium Test (PDT) Statistics: Combines PDT statistics from both selected common and rare variants to compute a composite OVPDT statistic.
• Permutation Procedure for P-value Calculation: Uses permutation testing to calculate p-values and maintain accurate type I error rates.

Scientific Applications:

• Family-based association testing: Identification of genetic variants associated with complex diseases using pedigree sequencing data.
• Joint analysis of common and rare variants: Assessment of combined contributions of common and rare variants, including risk, neutral, or protective effects.
• Simulation-based evaluation: Evaluation of type I error rates and comparative power when both common and rare variants influence disease in a region.

Methodology:

Computational steps explicitly include combining an Ordered Subset algorithm that prioritizes high-risk common variants (relative risks from parental mating types), a Variable Threshold algorithm that searches for an optimal allele frequency threshold for rare variants, combining PDT statistics from selected variants into the OVPDT statistic, and using a permutation procedure to calculate p-values.