Issue |
Genet. Sel. Evol.
Volume 33, Number 2, March-April 2001
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Page(s) | 133 - 152 | |
DOI | https://doi.org/10.1051/gse:2001113 |
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Genet. Sel. Evol. 33 (2001) 133-152
Bayes factors for detection of Quantitative Trait Loci
Luis Varonaa, Luis Alberto García-Cortésb and Miguel Pérez-Encisoaa 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