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Bioinformatics Advance Access published online on January 12, 2006
Bioinformatics, doi:10.1093/bioinformatics/btk050
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received October 20, 2005
Revised January 5, 2006
Accepted January 9, 2006

Article

Multiple association analysis via simulated annealing (MASSA)

M. Pérez-Enciso 1 *

1 Institut Catalá de Reçerca i Estudis Avançats, Pg Lluis Companys 23, 08010 Barcelona, Spain; Departament de Ciència Animal i del Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain

* To whom correspondence should be addressed.
M. Pérez-Enciso, E-mail: miguel.perez{at}uab.es


  Abstract

Summary: Genome-wide association studies are now technically feasible and likely to become a fundamental tool in unraveling the ultimate genetic basis of complex traits. However, new statistical and computational methods need to be developed to extract the maximum information in a realistic computing time. Here we propose a new method for multiple association analysis via simulated annealing that allows for epistasis and any number of markers. It consists of finding the model with lowest Bayesian Information Criterion using simulated annealing. The data are described by means of a mixed model and new alternative models are proposed using a set of rules, e.g., new sites can be added (or deleted), or new epistatic interactions can be included between existing genetic factors. The method is illustrated with simulated and real data.

Availability: An executable version of the program (MASSA) running under the Linux OS is freely available, together with documentation, at http://www.icrea.es/pag.asp?id=Miguel.Perez.

Associate Editor: Frank Dudbridge
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