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Bayesian inference in genetic analysis of diploid populations: inbreeding coefficient and outcrossing rate estimation

The Bayesian methodology was used to estimate the inbreeding coefficient and outcrossing rate in diploid populations by COCKERHAM random model to allelic frequency. The proposed methodology was evaluated by data simulation. The Gibbs Sampler algorithm was implemented in the R statistical software to obtain the random samples of the inbreeding coefficient and outcrossing rate posteriors marginal distributions. The Bayesian method showed good results, because the 95% credible intervals contained the true parameter values to all of the selected scenes. The Gibbs Sampler convergence was checked and this validated the estimation results.

genetic parameters; Gibbs Sampler; simulated data


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