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Publication : An efficient Bayesian model selection approach for interacting quantitative trait loci models with many effects.

First Author  Yi N Year  2007
Journal  Genetics Volume  176
Issue  3 Pages  1865-77
PubMed ID  17483424 Mgi Jnum  J:175514
Mgi Id  MGI:5285893 Doi  10.1534/genetics.107.071365
Citation  Yi N, et al. (2007) An efficient Bayesian model selection approach for interacting quantitative trait loci models with many effects. Genetics 176(3):1865-77
abstractText  We extend our Bayesian model selection framework for mapping epistatic QTL in experimental crosses to include environmental effects and gene-environment interactions. We propose a new, fast Markov chain Monte Carlo algorithm to explore the posterior distribution of unknowns. In addition, we take advantage of any prior knowledge about genetic architecture to increase posterior probability on more probable models. These enhancements have significant computational advantages in models with many effects. We illustrate the proposed method by detecting new epistatic and gene-sex interactions for obesity-related traits in two real data sets of mice. Our method has been implemented in the freely available package R/qtlbim (http://www.qtlbim.org) to facilitate the general usage of the Bayesian methodology for genomewide interacting QTL analysis.
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