Niche harmony search algorithm for detecting complex disease associated high-order SNP combinations.

ABSTRACT: Genome-wide association study is especially challenging in detecting high-order disease-causing models due to model diversity, possible low or even no marginal effect of the model, and extraordinary search and computations. In this paper, we propose a niche harmony search algorithm where joint entropy is utilized as a heuristic factor to guide the search for low or no marginal effect model, and two computationally lightweight scores are selected to evaluate and adapt to diverse of disease models. In order to obtain all possible suspected pathogenic models, niche technique merges with HS, which serves as a taboo region to avoid HS trapping into local search. From the resultant set of candidate SNP-combinations, we use G-test statistic for testing true positives. Experiments were performed o

SUBMITTER: Tuo S 

PROVIDER: S-EPMC5599559 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature