MdrPDT

MdrPDT integrates Multifactor Dimensionality Reduction (MDR) and the Genotype-Pedigree Disequilibrium Test (geno-PDT) to detect and analyze high-order gene-gene and gene-environment interactions in familial and case-control genetic data.

Key Features:

• Integration of MDR and geno-PDT: Integrates Multifactor Dimensionality Reduction (MDR) and the Genotype-Pedigree Disequilibrium Test (geno-PDT) to combine nonparametric interaction detection with within-family genotype-disease association testing.
• High-order interaction detection: Detects high-order gene-gene and gene-environment interactions that may lack marginal main effects.
• Family-structure support: Analyzes diverse family structures, including nuclear families, without requiring selection of a single matched pair per family such as discordant sibling pairs or triads.
• Single-locus and multilocus effects: Identifies both single-locus effects and joint effects involving multiple loci.
• Addresses parametric limitations: Addresses limitations of traditional parametric methods, particularly challenges with sparse data scenarios.
• Simulation-based validation: Employs simulations to validate performance and assess statistical power.
• Application to Alzheimer disease: Has been applied to analyze candidate genes for Alzheimer disease (AD) in a large family dataset.
• Within-family genotype association: Evaluates genotype-disease associations within nuclear families using geno-PDT.

Scientific Applications:

• Interaction discovery in complex diseases: Detection of high-order gene-gene and gene-environment interactions in multifactorial disease studies.
• Family-based association analysis: Family-based genotype-disease association testing across nuclear families.
• Candidate gene analysis for AD: Analysis of candidate genes for Alzheimer disease (AD) in large family cohorts.
• Method validation and power assessment: Validation of interaction-detection performance and statistical power estimation via simulations.

Methodology:

Integrates MDR with geno-PDT for combined interaction detection and within-family association testing, and uses simulations to validate effectiveness and assess statistical power.