RESEARCH ARTICLE
On the Informativeness of Dominant and Co-Dominant Genetic Markers for Bayesian Supervised Clustering
Gilles Guillot*, 1, Alexandra Carpentier-Skandalis2
1 Department of Informatics and Mathematical Modelling, Technical University of Denmark, 2800, Lyngby, Copenhagen, Denmark.
2 Centre for Ecological and Evolutionary Synthesis, Department of Biology, University of Oslo, P.O. Box 1066 Blindern, 0316 Oslo, Norway
Article Information
Identifiers and Pagination:
Year: 2011Volume: 3
First Page: 7
Last Page: 12
Publisher Id: TOSPJ-3-7
DOI: 10.2174/1876527001103010007
Article History:
Received Date: 29/7/2010Revision Received Date: 15/10/2010
Acceptance Date: 18/11/2010
Electronic publication date: 30/3/2011
Collection year: 2011
© 2011 Guillot et al.;
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
We study the accuracy of a Bayesian supervised method used to cluster individuals into genetically homogeneous groups on the basis of dominant or codominant molecular markers. We provide a formula relating an error criterion to the number of loci used and the number of clusters. This formula is exact and holds for arbitrary number of clusters and markers. Our work suggests that dominant markers studies can achieve an accuracy similar to that of codominant markers studies if the number of markers used in the former is about 1.7 times larger than in the latter.
Keywords: Assigment method, multilocus genotype, SNP, AFLP, likelihood, Bayes estimator..
