Format

Send to

Choose Destination
PLoS One. 2011;6(6):e21014. doi: 10.1371/journal.pone.0021014. Epub 2011 Jun 28.

On identifying the optimal number of population clusters via the deviance information criterion.

Author information

1
Stanford Genome Technology Center and Department of Biochemistry, Stanford University, Stanford, California, United States of America. hgao98@stanford.edu

Abstract

Inferring population structure using bayesian clustering programs often requires a priori specification of the number of subpopulations, K, from which the sample has been drawn. Here, we explore the utility of a common bayesian model selection criterion, the Deviance Information Criterion (DIC), for estimating K. We evaluate the accuracy of DIC, as well as other popular approaches, on datasets generated by coalescent simulations under various demographic scenarios. We find that DIC outperforms competing methods in many genetic contexts, validating its application in assessing population structure.

PMID:
21738600
PMCID:
PMC3125185
DOI:
10.1371/journal.pone.0021014
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Public Library of Science Icon for PubMed Central
Loading ...
Support Center