Detecting the number of clusters of individuals using the softwarestructure: a simulation study

Authors: EVANNO, G.; REGNAUT, S.; GOUDET, J.

Source: Molecular Ecology, Volume 14, Number 8, July 2005 , pp. 2611-2620(10)

Buy & download fulltext article:

Price: $48.00 plus tax (Refund Policy)

Abstract:

The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the softwarestructureallows 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 Delta

K based on the rate of change in the log probability of data between successive K values, we found thatstructureaccurately 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: AFLP; hierarchical structure; microsatellite; simulations; structuresoftware

Document Type: Research article

DOI: http://dx.doi.org/10.1111/j.1365-294X.2005.02553.x

Affiliations: 1: Department of Ecology and Evolution, Biology building, University of Lausanne, CH 1015 Lausanne, Switzerland

Publication date: 2005-07-01