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A novel strategy for detecting multiple loci in Genome-Wide Association Studies of complex diseases
1Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH 44106, USA. jingli@eecs.case.edu
Abstract:
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.
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