Bayesian clustering algorithms ascertaining spatial population structure: a new computer program and a comparison study
Top Cited Papers
- 6 April 2007
- journal article
- research article
- Published by Wiley in Molecular Ecology Notes
- Vol. 7 (5) , 747-756
- https://doi.org/10.1111/j.1471-8286.2007.01769.x
Abstract
On the basis of simulated data, this study compares the relative performances of the Bayesian clustering computer programsstructure,geneland,geneclustand a new program namedtess. While these four programs can detect population genetic structure from multilocus genotypes, only the last three ones include simultaneous analysis from geographical data. The programs are compared with respect to their abilities to infer the number of populations, to estimate membership probabilities, and to detect genetic discontinuities and clinal variation. The results suggest that combining analyses usingtessandstructureoffers a convenient way to address inference of spatial population structure.Keywords
This publication has 25 references indexed in Scilit:
- fastruct: model‐based clustering made fasterMolecular Ecology Notes, 2006
- Bayesian Clustering Using Hidden Markov Random Fields in Spatial Population GeneticsGenetics, 2006
- Computer programs for population genetics data analysis: a survival guideNature Reviews Genetics, 2006
- Genetic structure is influenced by landscape features: empirical evidence from a roe deer populationMolecular Ecology, 2006
- Low Levels of Genetic Divergence across Geographically and Linguistically Diverse Populations from IndiaPLoS Genetics, 2006
- Clines, Clusters, and the Effect of Study Design on the Inference of Human Population StructurePLoS Genetics, 2005
- Detecting the number of clusters of individuals using the software structure: a simulation studyMolecular Ecology, 2005
- FAST‐TRACK: Integrating QTL mapping and genome scans towards the characterization of candidate loci under parallel selection in the lake whitefish (Coregonus clupeaformis)Molecular Ecology, 2004
- EM procedures using mean field-like approximations for Markov model-based image segmentationPattern Recognition, 2003
- Genetic Structure of Human PopulationsScience, 2002