DOI: 10.1051/gse:2001113

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Genet. Sel. Evol. 33 (2001) 133-152

Bayes factors for detection of Quantitative Trait Loci

Luis Varona^a, Luis Alberto García-Cortés^b and Miguel Pérez-Enciso<sup>a

a</sup>  Area de Producció Animal, Centre UdL-IRTA, c/ Rovira Roure 177, 25198 Lleida, Spain
^b  Unidad de Genética Cuantitativa y Mejora Animal, Universidad de Zaragoza, 50013 Zaragoza, Spain

(Received 8 November 1999; accepted 24 October 2000)

Abstract
A fundamental issue in quantitative trait locus (QTL) mapping is to determine the plausibility of the presence of a QTL at a given genome location. Bayesian analysis offers an attractive way of testing alternative models (here, QTL vs. no-QTL) via the Bayes factor. There have been several numerical approaches to computing the Bayes factor, mostly based on Markov Chain Monte Carlo (MCMC), but these strategies are subject to numerical or stability problems. We propose a simple and stable approach to calculating the Bayes factor between nested models. The procedure is based on a reparameterization of a variance component model in terms of intra-class correlation. The Bayes factor can then be easily calculated from the output of a MCMC scheme by averaging conditional densities at the null intra-class correlation. We studied the performance of the method using simulation. We applied this approach to QTL analysis in an outbred population. We also compared it with the Likelihood Ratio Test and we analyzed its stability. Simulation results were very similar to the simulated parameters. The posterior probability of the QTL model increases as the QTL effect does. The location of the QTL was also correctly obtained. The use of meta-analysis is suggested from the properties of the Bayes factor.

Key words: Bayes factor / Quantitative Trait Loci / hypothesis testing / Markov Chain Monte Carlo

Correspondence and reprints: Luis Varona Luis.varona@irta.es

© INRA, EDP Sciences 2001