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Simple f test reveals gene-gene interactions in case-control studies.


ABSTRACT: 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.

SUBMITTER: Chen G 

PROVIDER: S-EPMC3399554 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Simple f test reveals gene-gene interactions in case-control studies.

Chen Guanjie G   Yuan Ao A   Zhou Jie J   Bentley Amy R AR   Adeyemo Adebowale A   Rotimi Charles N CN  

Bioinformatics and biology insights 20120702


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  ...[more]

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