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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) algorith...

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Detalles Bibliográficos
Autores principales: Wang, Yupeng, Liu, Xinyu, Robbins, Kelly, Rekaya, Romdhane
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2880958/
https://www.ncbi.nlm.nih.gov/pubmed/20426808
http://dx.doi.org/10.1186/1756-0500-3-117
Descripción
Sumario: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.