AprioriGWAS, a new pattern mining strategy for detecting genetic variants associated with disease through interaction effects.

ABSTRACT: Identifying gene-gene interaction is a hot topic in genome wide association studies. Two fundamental challenges are: (1) how to smartly identify combinations of variants that may be associated with the trait from astronomical number of all possible combinations; and (2) how to test epistatic interaction when all potential combinations are available. We developed AprioriGWAS, which brings two innovations. (1) Based on Apriori, a successful method in field of Frequent Itemset Mining (FIM) in which a pattern growth strategy is leveraged to effectively and accurately reduce search space, AprioriGWAS can efficiently identify genetically associated genotype patterns. (2) To test the hypotheses of epistasis, we adopt a new conditional permutation procedure to obtain reliable statistical inference

SUBMITTER: Zhang Q 

PROVIDER: S-EPMC4046917 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature