Analytical bayesian approach for assigning individuals to populations

The Journal of Heredity
L BaudouinJ-M Cornuet

Abstract

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.

Citations

Nov 25, 2005·Journal of Computational Biology : a Journal of Computational Molecular Cell Biology·Noah A Rosenberg
Oct 19, 2006·PLoS Genetics·Michael F SeldinPeter K Gregersen
Jul 22, 2011·Genetics·Sang Chul Choi, Jody Hey
Jul 22, 2014·Journal of Forensic Sciences·María E FernándezGuillermo Giovambattista
Dec 1, 2007·Meat Science·C DalvitM Cassandro
Nov 20, 2008·Animal Genetics·R NegriniP Ajmone Marsan
Aug 2, 2006·Animal Genetics·J CañónUNKNOWN ECONOGENE Consortium
May 12, 2010·Molecular Ecology·Alisa P RamakrishnanMitchell B Cruzan
Apr 25, 2015·Nature Communications·Daril A Vilhena, Alexandre Antonelli

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