The Performance of Conditional Tests for Family Data in Associated Regions Derived from GWAS
Background Genome wide association studies (GWAS) have been used successfully to identify genetic loci associated with complex diseases and phenotypes Often this association lakes the form of several significant signals (such as small p values) in a univariate analysis at various markers within a single genetic region Once confirmed, these associations lead to the question if a single marker tags the association signal of another, functonally relevant variant or if the single marker tags a functionally relevant haplo type To deal with this question methods for family data based on logistic regression adaptations of the transmission/disequilibrium test (TDT) or weighted haplotype likeli hood (WHL) methods have been proposed in the literature Objectives Objectives were to examine the effect of parameters such as sample size, in heritance model and the effects of linkage disequilibrium (LD) in the region on the ability of a selection of methods to detect an independent effect from an additional locus Methods All methods tested were applied to simulated genetic data of trios comprising a single affected offspring and two parents Results While regression based methods have advantages such as model flexibility potentially increasing power the WHL method was more robust against increasing LD in the scenarios analyzed Conclusions Simulation results suggest that the regression and WHL methods are better able with regard to statistical power than the adaptation of the TDT analyzed here to detect genetic effects at an additional locus while controlling for confounding at another locus
disequilibrium haplotype genetic association analysis nuclear family genetic models linkage