Work

Detecting Epistatic SNPs Associated with Complex Diseases via a Bayesian Classification Tree Search Method

Year: 2010

Type: article

Abstract: Complex phenotypes are known to be associated with interactions among genetic factors. A growing body of evidence suggests that gene-gene interactions contribute to many common human diseases. Identifying potential interactions of multiple polymorphisms thus may be important to understand the biology and biochemical processes of the disease etiology. However, despite the great success of genome-wide association studies that mostly focus on single locus analysis, it is challenging to detect these interactions, especially when the marginal effects of the susceptible loci are weak and/or they involve several genetic factors. Here we describe a Bayesian classification tree model to detect such interactions in case-control association studies. We show that this method has the potential to uncover interactions involving polymorphisms showing weak to moderate marginal effects as well as multi-factorial interactions involving more than two loci.

Source: Annals of Human Genetics

DOI: 10.1111/j.1469-1809.2010.00627.x

Authors: Min Chen, Judy Cho, Hongyu Zhao

Institutions: The University of Texas Southwestern Medical Center, Yale University

Language: English

Topic: Genetic Associations and Epidemiology

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, National Institute of General Medical Sciences, National Institute of Diabetes and Digestive and Kidney Diseases, National Center for Research Resources