AntEpiSeeker: detecting epistatic interactions for case-control studies using a two-stage ant colony optimization algorithm
Date
2010-04-28Author
Wang, Yupeng
Liu, Xinyu
Robbins, Kelly
Rekaya, Romdhane
Metadata
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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.