Efficient and Fast Analysis for Detecting High Order Gene-by-Gene Interactions in a Genome-Wide Association Study

Abstract

Most common complex traits are affected by multiple genes and/or environmental factors. To understand genetic architecture of complex traits, the investigation of gene-gene and gene-environment interactions can be essential. However, conducting gene-gene interaction using genome-wide data requires exploring a huge search space and suffers from a computation burden due to high dimensionality of genetic data. To identify gene-gene interaction more efficiently, we propose a gene-based reduction method which first summarizes the gene effect by combining multiple single nucleotide polymorphism (SNP) and then performs the gene-gene interaction via the summarized gene effect. By reducing the search space from SNPs to gene, our gene-based method becomes efficient and fast for identifying gene-gene interaction in genome wide association studies. The gene-based reduction method is illustrated by hypertension data from a Korean population.