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A Markov chain Monte Carlo strategy for sampling from the joint posterior distribution of pedigrees and population parameters under a Fisher-Wright model with partial selfing

Lookup NU author(s): Dr Ian Wilson

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Abstract

A simple population genetic model is presented for a hermaphrodite annual species, allowing both selfing and outcrossing. Those male gametes (pollen) responsible for outcrossing are assumed to disperse much further than seeds. Under this model, the pedigree of a sample from a single locality is loop-free. A novel Markov chain Monte Carlo strategy is presented for sampling from the joint posterior distribution of the pedigree of such a sample and the parameters of the population genetic model (including the selfing rate) given the genotypes of the sampled individuals at unlinked marker loci. The computational costs of this Markov chain Monte Carlo strategy scale well with the number of individuals in the sample, and the number of marker loci, but increase exponentially with the age (time since colonisation from the source population) of the local population. Consequently, this strategy is particularly suited to situations where the sample has been collected from a population which is the result of a recent colonisation process. © 2007 Elsevier Inc. All rights reserved.

Publication metadata

Author(s): Wilson IJ, Dawson KJ

Publication type: Article

Publication status: Published

Journal: Theoretical Population Biology

Year: 2007

Volume: 72

Issue: 3

Pages: 436-458

ISSN (print): 0040-5809

ISSN (electronic): 1096-0325

Publisher: Academic Press

URL: http://dx.doi.org/10.1016/j.tpb.2007.03.002

DOI: 10.1016/j.tpb.2007.03.002

PubMed id: 17448511

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