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Título:
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Bayes factors for detection of quantitative trait loci
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Autor/a:
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Varona Aguado, Luís; García Cortés, Luis Alberto; Perez Enciso, Miguel
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Notas:
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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. |
Materia(s):
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-Bayes factor -Quantitative Trait Loci -Hypothesis testing |
Derechos:
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cc-by (c) Varona et al., 2001
http://creativecommons.org/licenses/by/3.0/es/
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Tipo de documento:
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article publishedVersion |
Editor:
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BioMed Central
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