Subset-based ant colony optimisation for the discovery of gene-gene interactions in genome wide association studies

Authors:
Emmanuel Sapin;Ed Keedwell;Tim Frayling
Affiliations:
University of Exeter, Exeter, United Kingdom;University of Exeter, Exeter, United Kingdom;Institute of Biomedical and Clinical Science, Peninsula Medical School, Magdalen Road, Exeter, United Kingdom
Venue:
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Year:
2013

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Abstract

In this paper an ant colony optimisation approach for the discovery of gene-gene interactions in genome-wide association study (GWAS) data is proposed. The subset-based approach includes a novel encoding mechanism and tournament selection to analyse full scale GWAS data consisting of hundreds of thousands of variables to discover associations between combinations of small DNA changes and Type II diabetes. The method is tested on a large established database from the Wellcome Trust Case Control Consortium and is shown to discover combinations that are statistically significant and biologically relevant within reasonable computational time.