AntEpiSeeker: Detecting epistatic interactions for case-control studies using a two-stage ant colony optimization algorithm

Abstract

Background. Epistatic interactions of multiple single nucleotide polymorphisms (SNPs) are now believed to affect individual susceptibility to common diseases. The detection of such interactions, however, is a challenging task in large scale association studies. Ant colony optimization (ACO) algorithms have been shown to be useful in detecting epistatic interactions. Findings. AntEpiSeeker, a new two-stage ant colony optimization algorithm, has been developed for detecting epistasis in a case-control design. Based on some practical epistatic models, AntEpiSeeker has performed very well. Conclusions. AntEpiSeeker is a powerful and efficient tool for large-scale association studies and can be downloaded from http://nce.ads.uga.edu/∼romdhane/ AntEpiSeeker/index.html. © 2010 Rekaya et al; licensee BioMed Central Ltd.