Abstract
Next-generation sequencing (NGS) has been widely used in genetic association studies to identify both common and rare variants associated with complex diseases. Various statistical association tests have been developed to analyze NGS data; however, most focus on identifying the marginal effects of a set of genetic variants on the disease. Only a few association tests for NGS data analysis have considered the interaction effects between genes. We developed three powerful gene-based gene-gene interaction tests for testing both the main effects and the interaction effects of common, low-frequency, and common with low-frequency variant pairs between two genes (the IGOF tests) in case-control studies using NGS data. We performed a comprehensive simulation study to verify that the proposed tests had appropriate type I error rates and significantly higher power than did other interaction tests for analyzing NGS data. The tests were applied to a whole-exome sequencing dataset for autism spectrum disorder (ASD) and the significant results were evaluated in another independent ASD cohort. The IGOF tests were implemented in C++ and are available at http://igof.sourceforge.net.
Highlights
Next-generation sequencing (NGS) has become a popular technology used in genetic studies to identify rare variants as well as common variants associated with complex diseases
We evaluated the 10 most significant interaction pairs identified by the IGOFcombined test in another genome-wide association study (GWAS) dataset for autism obtained from the Autism Genome Project (AGP) (Autism Genome Project et al, 2007; Anney et al, 2010; Pinto et al, 2010)
We developed the IGOFcommon, IGOFLF, and IGOFcombined tests, which are powerful gene-based interaction tests for common, LF, and common combined with LF variant pairs, respectively
Summary
Next-generation sequencing (NGS) has become a popular technology used in genetic studies to identify rare variants (i.e., genetic variants with minor allele frequencies
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