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Title: SNPHarvester : a filtering method for detecting epistatic interactions in genome-wide association studies
Authors: Yang, Can
He, Zengyou
Wan, Xiang
Yang, Qiang
Xue, Hong
Yu, Weichuan
Keywords: Genome-wide association (GWA)
Epistatic interactions
SNP-SNP interactions
Issue Date: 2008
Citation: Bioinformatics, v. 25, no. 4, February 2009, p. 504-511
Abstract: Motivation: Hundreds of thousands of single nucleotide polymorphisms (SNPs) are available for genome-wide association (GWA) studies nowadays. The epistatic interactions of SNPs are believed to be very important in determining individual susceptibility to complex diseases. However, existing methods for SNP interaction discovery either suffer from high computation complexity or perform poorly when marginal effects of disease loci are weak or absent. Hence, it is desirable to develop an effective method to search epistatic interactions in genome-wide scale. Results: We propose a new method SNPHarvester to detect SNP-SNP interactions in GWA studies. SNPHarvester creates multiple paths in which the visited SNP groups tend to be statistically associated with diseases, and then harvests those significant SNP groups which pass the statistical tests. It greatly reduces the number of SNPs such that existing tools can be used to detect epistatic interactions. By using a wide range of simulated data and a real genome-wide data, we demonstrate that SNPHavest outperforms its recent competitor significantly and is promising for practical disease prognosis.
Rights: This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Bioinformatics following peer review. The definitive publisher-authenticated version Bioinformatics, v. 25, no. 4, p. 504-511 is available online at : doi:10.1093/bioinformatics/btn652
Appears in Collections:BICH Journal/Magazine Articles
ECE Journal/Magazine Articles
CSE Journal/Magazine Articles

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