Detecting the number of clusters of individuals using the software structure: a simulation study

G. EVANNO; S. REGNAUT; J. Goudet

doi:10.1111/j.1365-294x.2005.02553.x

journal article Open Access May 11, 2005

Detecting the number of clusters of individuals using the software structure: a simulation study

G. EVANNO S. REGNAUT J. Goudet

Molecular Ecology Vol. 14 No. 8 pp. 2611-2620 · Wiley

View at Publisher Save 10.1111/j.1365-294x.2005.02553.x

Abstract

AbstractThe identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software structure allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual‐based model. We found that in most cases the estimated ‘log probability of data’ does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic ΔK based on the rate of change in the log probability of data between successive K values, we found that structure accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.

Keywords

Biochemistry, Genetics and Molecular Biology Mathematics Gene Biology Ecology Computer science Sample (material) Genetics Statistics Evolutionary biology Software Demography Genetic diversity and population structure Bayesian probability Population Genetic Mapping and Diversity in Plants and Animals Microsatellite Sample size determination Statistic Identification (biology) Homogeneous Biological dispersal Forensic and Genetic Research

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References

Details

Published: May 11, 2005
Vol/Issue: 14(8)
Pages: 2611-2620
License: View

Subjects

Biochemistry, Genetics and Molecular Biology

Authors

Cite This Article

G. EVANNO, S. REGNAUT, J. Goudet (2005). Detecting the number of clusters of individuals using the software structure: a simulation study. Molecular Ecology, 14(8), 2611-2620. https://doi.org/10.1111/j.1365-294x.2005.02553.x

Detecting the number of clusters of individuals using the software structure: a simulation study

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