Bayes factors for detection of quantitative trait loci
Varona Aguado, Luís
García Cortés, Luis Alberto
Perez Enciso, Miguel
MetadataShow full item record
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.
Is part ofGenetics Selection Evolution, 2001, vol. 33, p. 133-152
European research projects
The following license files are associated with this item:
Showing items related by title, author, creator and subject.
García Cortés, Luis Alberto; Cabrillo, Carlos; Moreno, Carlos; Varona Aguado, Luís (BioMed Central, 2001)The testing of Bayesian point null hypotheses on variance component models have resulted in a tough assigmment for which no clear and generally accepted method exists. In this work we present what we believe is a succeeding ...
Computation of identity by descent probabilities conditional on DNA markers via a Monte Carlo Markov Chain method Perez Enciso, Miguel; Varona Aguado, Luís; Rothschild, Max Frederick (BioMed Central, 2000)The accurate estimation of the probability of identity by descent (IBD) at loci or genome positions of interest is paramount to the genetic study of quantitative and disease resistance traits. We present a Monte Carlo ...
Bayes factor for testing between different structures of random genetic groups: A case study using weaning weight in Bruna dels Pirineus beef cattle Casellas, Joaquim; Piedrafita, Jesús; Varona Aguado, Luís (BioMed Central, 2007)The implementation of genetic groups in BLUP evaluations accounts for different expectations of breeding values in base animals. Notwithstanding, many feasible structures of genetic groups exist and there are no analytical ...