%0 Journal Article
%T Simple F Test Reveals Gene-Gene Interactions in Case-Control Studies
%A Guanjie Chen
%A Ao Yuan
%A Jie Zhou
%A Amy R. Bentley
%A Adebowale Adeyemo and Charles N. Rotimi
%J Bioinformatics and Biology Insights
%D 2012
%I 
%R 10.4137/BBI.S9867
%X Missing heritability is still a challenge for Genome Wide Association Studies (GWAS). Gene-gene interactions may partially explain this residual genetic influence and contribute broadly to complex disease. To analyze the gene-gene interactions in case-control studies of complex disease, we propose a simple, non-parametric method that utilizes the F-statistic. This approach consists of three steps. First, we examine the joint distribution of a pair of SNPs in cases and controls separately. Second, an F-test is used to evaluate the ratio of dependence in cases to that of controls. Finally, results are adjusted for multiple tests. This method was used to evaluate gene-gene interactions that are associated with risk of Type 2 Diabetes among African Americans in the Howard University Family Study. We identified 18 gene-gene interactions (P < 0.0001). Compared with the commonly-used logistical regression method, we demonstrate that the F-ratio test is an efficient approach to measuring gene-gene interactions, especially for studies with limited sample size.
%U http://www.la-press.com/simple-f-test-reveals-gene-gene-interactions-in-case-control-studies-article-a3244