Li Jing
Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH 44106, USA.
Int J Bioinform Res Appl. 2008;4(2):150-63. doi: 10.1504/IJBRA.2008.018342.
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.