Gene-gene interaction analysis for quantitative trait using cluster-based multifactor dimensionality reduction method

With recent advances in high-throughput genotyping techniques, many genome-wide association studies have been conducted to understand the relationship between genes and complex diseases. Though single SNP analysis is common for many genetic studies, this approach has a limitation in explaining genetic changes in complex diseases. Most complex diseases cannot be explained by a single gene mutation, and lack of success in many genetic studies could be attributed to gene-gene interactions. Although various methods have been developed to identify gene-gene interactions for binary traits, few statistical methods are currently available for determining the genetic interactions associated with quantitative traits. To address this problem, we propose CL-MDR method. It is a modified version of multifactor dimensionality reduction for quantitative traits. The proposed method was examined by simulation studies, which showed that CL-MDR successfully identified interactions associated with quantitative traits. We have also applied our approach to a Korean GWAS data for illustration.