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  • 1
    Electronic Resource
    Electronic Resource
    A Monte Carlo method for Bayesian analysis of linkage between single markers and quantitative trait loci. I. Methodology (1996)
    Springer
    Theoretical and applied genetics 93 (1996), S. 1161-1166 
    Details
    ISSN: 1432-2242
    Keywords: Key words Linkage analysis ; Bayesian method ; Markov chain Monte Carlo ; Quantitative-trait loci
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract A Bayesian approach to the statistical mapping of Quantitative Trait Loci (QTLs) using single markers was implemented via Markov Chain Monte Carlo (MCMC) algorithms for parameter estimation and hypothesis testing. Parameter estimators were marginal posterior means computed using a Gibbs sampler with data augmentation. Variables sampled included the augmented data (marker-QTL genotypes, polygenic effects), an indicator variable for linkage, and the parameters (allele frequency, QTL substitution effect, recombination rate, polygenic and residual variances). Several MCMC algorithms were derived for computing Bayesian tests of linkage, which consisted of the marginal posterior probability of linkage and the marginal likelihood of the QTL variance associated with the marker.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/s001220050351
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    Paper (German National Licenses)
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  • 2
    Electronic Resource
    Electronic Resource
    A Monte Carlo method for Bayesian analysis of linkage between single markers and quantitative trait loci. II. A simulation study (1996)
    Springer
    Theoretical and applied genetics 93 (1996), S. 1167-1174 
    Details
    ISSN: 1432-2242
    Keywords: Key words Linkage analysis ; Bayesian method ; Markov chain Monte Carlo ; Quantitative-trait loci ; Simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract A Bayesian approach to the statistical mapping of Quantitative Trait Loci (QTLs) using single markers was implemented via Markov Chain Monte Carlo (MCMC) algorithms for parameter estimation and hypothesis testing. Parameters were estimated by marginal posterior means computed with a Gibbs sampler with data augmentation. Variables sampled included the augmented data (marker-QTL genotypes, polygenic effects), the event of linkage or nonlinkage, and the parameters (allele frequencies, QTL substitution effect, recombination rate, polygenic and residual variances). The analysis was evaluated empirically via application to simulated granddaughter designs consisting of 2000 sons, 20 related sires and their ancestors. Results obtained in this study and preliminary work on multiple linked markers and multiple QTLs support the usefulness of the Bayesian method for the statistical mapping of QTLs.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/s001220050352
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
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