A novel strategy for detecting multiple loci in Genome-Wide Association Studies of complex diseases.
Large-scale Genome-Wide Association Studies (GWAS) for complex diseases are increasingly common, due to recent advances in genotyping technology. Gene-gene interactions play an important role in the etiology of complex diseases and have to be addressed in GWAS. In this paper, an efficient strategy based on two-stage analysis is proposed. It combines a single-locus approach with a Goodness-Of-Fit (GOF) test in stage one, and selects a promising subset of SNPs to be modelled using a full interaction model in stage two. Extensive simulations using different disease models with different levels of epistasis demonstrate that it achieves higher power than existing approaches.
Li
Jing
J
Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH 44106, USA. jingli@eecs.case.edu
D002874:Chromosome Mapping; D030342:Genetic Diseases, Inborn / Q000235:genetics*; D015894:Genome, Human; D006801:Humans; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide