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Comparative Study
. 2009 Nov 14:2009:673-7.

A Bayesian method for identifying genetic interactions

Shyam Visweswaran  1 , An-Kwok Ian Wong, M Michael Barmada
Affiliations
Comparative Study

A Bayesian method for identifying genetic interactions

Shyam Visweswaran et al. AMIA Annu Symp Proc. .

Abstract

An important challenge in the analysis of single nucleotide polymorphism (SNP) data is the identification of SNPs that interact in a nonlinear fashion in their association with disease. Such epistatic interactions among genetic variants at multiple loci likely underlie the inheritance of common diseases. We have developed a novel method called the Bayesian combinatorial method (BCM) for detecting combination of genetic variants that are predictive of disease. When compared with the multifactor dimensionality reduction (MDR), a widely used combinatorial method, BCM has significantly greater power to detect interactions and is computationally more efficient.

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Figures

Figure 1.
Figure 1.
A 2-locus epistatic model based on the M170 genetic model from [2]. Genotype frequencies are in parentheses and the penetrance values are in the cells.
Figure 2.
Figure 2.
An example of a table of counts for a 2-SNP combinatorial model for a dataset of 200 samples.
See this image and copyright information in PMC

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