QTDT

QTDT performs quantitative transmission disequilibrium testing to map complex-disease loci by analyzing linkage disequilibrium for quantitative and discrete traits in nuclear families and extended pedigrees with or without parental genotypes.

Key Features:

• Versatile Family Analysis: Analyzes nuclear families of any size and extended pedigrees, permitting inclusion or exclusion of parental genotypes for quantitative and discrete traits.
• Variance Components and Bias-Free Testing: Uses variance-component models to construct tests that leverage information from all available offspring and remain unbiased in the presence of linkage or familiality.
• Permutation Test for Accurate P-values: Implements permutation testing to obtain exact p-values and address bias in maximum-likelihood estimates of variance components when testing multiple linked polymorphisms.
• Power and Error Rate Analysis: Evaluates power and error rates via simulation studies, including scenarios that violate multivariate normality assumptions.
• Linkage Disequilibrium Mapping: Harnesses linkage disequilibrium over short distances to support high-resolution mapping and fine-mapping in dense genetic maps.
• Family Structure Considerations: Quantifies effects of parental genotyping and sibship size on power, noting minimal power loss when parents are genotyped and modest reductions without parents that are small if four or more offspring are genotyped; also reports fewer total genotypes needed to achieve comparable power when parents are ungenotyped but siblings are available.

Scientific Applications:

• Complex-disease gene mapping: High-resolution mapping of complex-disease genes in outbred populations using linkage disequilibrium and family-based association tests.
• Fine-mapping in dense genetic maps: Pinpointing disease-associated variants over short genomic distances by leveraging LD in dense marker sets.
• Study design evaluation: Assessing power and error rates for family-based association studies via simulation, including impacts of missing parental genotypes and deviations from multivariate normality.

Methodology:

Implements variance-component models with maximum-likelihood estimation, permutation testing for p-values, and simulation studies; analyzes quantitative and discrete traits in nuclear families (with or without parental genotypes) and extended pedigrees.