On the application of estimation of distribution algorithms to multi-marker tagging SNP selection

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“On the application of estimation of distribution algorithms to multi-marker tagging SNP selection” by R. Santana, A. Mendiburu, N. Zaitlen, E. Eskin, and J. A. Lozano, Department of Computer Science and Artificial Intelligence. University of the Basque Country technical report EHU-KZAA-IK-4/09, July 2009.

Abstract

This paper presents an algorithm for the automatic selection of a minimal subset of tagging single nucleotide polymorphisms (SNPs) using an estimation of distribution algorithm (EDA). The EDA stochastically searches the constrained space of possible feasible solutions and takes advantage of the underlying topological structure defined by the SNP correlations to model the problem interactions. The algorithm is evaluated across the HapMap reference panel data sets. The introduced algorithm is effective for the identification of minimal multi-marker SNP sets, which considerably reduce the dimension of the tagging SNP set in comparison with single-marker sets. New reduced tagging sets are obtained for all the HapMap SNP regions considered. We also show that the information extracted from the interaction graph representing the correlations between the SNPs can help to improve the efficiency of the optimization algorithm.

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BibTeX entry:

@techreport{Santana_et_al:2009d,
   author = {R. Santana and A. Mendiburu and N. Zaitlen and E. Eskin and
	J. A. Lozano},
   title = {On the application of estimation of distribution algorithms to
	multi-marker tagging {SNP} selection},
   institution = {Department of Computer Science and Artificial
	Intelligence, University of the Basque Country},
   number = {EHU-KZAA-IK-4/09},
   month = jul,
   year = {2009}
}

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