OPTPDT

OPTPDT implements family-based multi-SNP association testing using a variable p-value threshold algorithm to identify jointly associated SNPs in genes or pathways.

Key Features:

• Family-Based Analysis: Uses general nuclear families to perform pedigree-based association testing.
• Variable P-value Threshold Algorithm: Selects an optimal subset of SNPs from a predefined SNP set by applying a variable p-value threshold.
• Permutation Procedure for Significance Assessment: Assesses statistical significance with a permutation procedure to control type I error.
• Powerful Multi-SNP Analysis: Demonstrates greater power than the set-based test in PLINK, the multi-SNP FBAT test, and the p-value based test GATES in comparisons reported by the authors.
• SNP Set Definition: Operates on SNP sets defined by biological knowledge such as genes or pathways.
• Validation by Simulation: Relies on simulation studies to confirm type I error control and evaluate power.

Scientific Applications:

• Gene-based and Pathway Association Analyses: Identifies sets of SNPs with collective impacts on disease phenotypes at the gene or pathway level.
• Secondary Analysis of GWAS: Applies to existing genome-wide association study (GWAS) datasets for family-based multi-SNP testing.
• Family-based Disease Mapping: Has been applied to a family-based autism GWAS where it identified MACROD2-AS1 with genome-wide significance.

Methodology:

Define a SNP set based on biological knowledge (e.g., genes or pathways), apply the variable p-value threshold algorithm to select an optimal SNP subset, assess significance with a permutation procedure, and validate type I error rates and power via simulation studies.