title: 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.
  
  
  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.
authors.affiliation: Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA. rrekaya@uga.edu.
authors.forename: Yupeng
authors.initials: Y
authors.lastname: Wang
authors.forename: Xinyu
authors.initials: X
authors.lastname: Liu
authors.forename: Kelly
authors.initials: K
authors.lastname: Robbins
authors.forename: Romdhane
authors.initials: R
authors.lastname: Rekaya