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


RESULTS
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.
Wang
Yupeng
Y
Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA. rrekaya@uga.edu.
Liu
Xinyu
X
Robbins
Kelly
K
Rekaya
Romdhane
R