Linkage disequilibrium study with a parallel adaptive GA

In this article, we model a linkage disequilibrium study (genomic study) as an optimization problem where a given objective function has to be optimized. The objective of the study is to discover haplotypes (associations of genetic markers) candidate to explain multi-factorial diseases such as diabetes or obesity. To determine what kind of algorithm will be able to solve this problem, we first study the specificities and the structure of the problem. Results of this study show that exact algorithms are not adapted to this specific problem and lead us to the development of a parallel dedicated adaptive multipopulation genetic algorithm that is able to find several haplotypes of different sizes. After describing the genomic problem, we present the dedicated genetic algorithm, its specificities, such as the use of several populations and its advanced mechanisms such as the adaptive choice of operators, random immigrants, and its parallel implementation. Results on a real dataset are given.

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