Detecting genome-wide epistases based on the clustering of relatively frequent items.

ABSTRACT:

Motivation

In genome-wide association studies (GWAS), up to millions of single nucleotide polymorphisms (SNPs) are genotyped for thousands of individuals. However, conventional single locus-based approaches are usually unable to detect gene-gene interactions underlying complex diseases. Due to the huge search space for complicated high order interactions, many existing multi-locus approaches are slow and may suffer from low detection power for GWAS.

Results

In this article, we develop a simple, fast and effective algorithm to detect genome-wide multi-locus epistatic interactions based on the clustering of relatively frequent items. Extensive experiments on simulated data show that our algorithm is fast and more powerful in general than some recently proposed methods. On a re

SUBMITTER: Xie M 

PROVIDER: S-EPMC3244765 | biostudies-literature | 2012 Jan

REPOSITORIES: biostudies-literature