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

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    Date
    2010-04-28
    Author
    Wang, Yupeng
    Liu, Xinyu
    Robbins, Kelly
    Rekaya, Romdhane
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    Abstract
    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.
    URI
    http://dx.doi.org/10.1186/1756-0500-3-117
    http://hdl.handle.net/10724/19693
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