Analytical bayesian approach for assigning individuals to populations
We propose a general formulation of the Bayesian method for assigning individuals to a population among a predetermined set of reference populations using molecular marker information. Compared to previously published methods, ours allows us to consider different types of prior information about allele frequencies by using a Dirichlet prior probability distribution. It also makes it possible to assign a set of individuals assumed to belong to the same population with increased accuracy using their pooled genotype data. The efficiency of the method is illustrated by application to a group of closely related coconut populations. An interesting feature of the Bayesian procedure is the way it handles imprecise information. With a poor or even incomplete dataset, assignment is still be possible and gives valid results: poor data quality is reflected in an ambiguous result rather than in a false conclusion.
| Main Authors: | , , |
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| Format: | article biblioteca |
| Language: | eng |
| Subjects: | F30 - Génétique et amélioration des plantes, U10 - Informatique, mathématiques et statistiques, méthode statistique, génétique des populations, http://aims.fao.org/aos/agrovoc/c_7377, http://aims.fao.org/aos/agrovoc/c_34326, |
| Online Access: | http://agritrop.cirad.fr/525219/ http://agritrop.cirad.fr/525219/1/525219.pdf |
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