Genome-wide association study (GWAS) has become a commonly adopted approach for revealing the genetic
architecture of complex diseases, with respect to uncovering the unknown genetic variants involved in the disease, their
variations in the population and the magnitude of their effects. Though a substantial number of disease-susceptibility variants
have been identified, the genetic architecture of complex diseases has remained elusive. It is unclear how many genetic
variants in the human genome are associated with diseases, and how the genetic variants interact with one another to
cause diseases. This challenge is partly due to the pervasive gene-gene interactions that underlie complex human diseases.
Whereas a number of statistical methods have been developed for detecting gene-gene interactions, they are designed for
various purposes, such as a particular study design, the order of the interactions being examined, and the measurement of
disease phenotypes. This paper provides a survey of the currently available statistical methods and patents from the perspective
of their application to various types of phenotypic traits. We also discuss the strength of each method as well as
the biological interpretation of results.
Keywords: Epistasis, statistical methods, genetic association study, phenotypic traits
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