A Bayesian method for identification of stock mixtures from molecular marker data

Corrander, Jukka and Marttinen, Pekka and Mäntyniemi, Samu (2006) A Bayesian method for identification of stock mixtures from molecular marker data. Fishery Bulletin, 104(4), pp. 550-558.

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Abstract

Molecular markers have been demonstrated to be useful for the estimation of stock mixture proportions where the origin of individuals is determined from baseline samples. Bayesian statistical methods are widely recognized as providing a preferable strategy for such analyses. In general, Bayesian estimation is based on standard latent class models using data augmentation through Markov chain Monte Carlo techniques. In this study, we introduce a novel approach based on recent developments in the estimation of genetic population structure. Our strategy combines analytical integration with stochastic optimization to identify stock mixtures. An important enhancement over previous methods is the possibility of appropriately handling data where only partial baseline sample information is available. We address the potential use of nonmolecular, auxiliary biological information in our Bayesian model.

Item Type: Article
Title: A Bayesian method for identification of stock mixtures from molecular marker data
Personal Creator/Author:
CreatorsEmail
Corrander, Jukka
Marttinen, Pekka
Mäntyniemi, Samu
Refereed: Yes
Journal or Publication Title: Fishery Bulletin
Volume: 104
Number: 4
Page Range: pp. 550-558
Date: 2006
ISSN: 0090-0656
Issuing Agency: United States National Marine Fisheries Service
Subjects: Biology
Ecology
Fisheries
Item ID: 8948
Depositing User: Patti M. Marraro
Date Deposited: 27 Jun 2012 19:29
Last Modified: 27 Jun 2012 19:29
URI: http://aquaticcommons.org/id/eprint/8948

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