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Clumpak: a program for identifying clustering modes and packaging population structure inferences across K

Clumpak: a program for identifying clustering modes and packaging population structure inferences... The identification of the genetic structure of populations from multilocus genotype data has become a central component of modern population‐genetic data analysis. Application of model‐based clustering programs often entails a number of steps, in which the user considers different modelling assumptions, compares results across different predetermined values of the number of assumed clusters (a parameter typically denoted K), examines multiple independent runs for each fixed value of K, and distinguishes among runs belonging to substantially distinct clustering solutions. Here, we present Clumpak (Cluster Markov Packager Across K), a method that automates the postprocessing of results of model‐based population structure analyses. For analysing multiple independent runs at a single K value, Clumpak identifies sets of highly similar runs, separating distinct groups of runs that represent distinct modes in the space of possible solutions. This procedure, which generates a consensus solution for each distinct mode, is performed by the use of a Markov clustering algorithm that relies on a similarity matrix between replicate runs, as computed by the software Clumpp. Next, Clumpak identifies an optimal alignment of inferred clusters across different values of K, extending a similar approach implemented for a fixed K in Clumpp and simplifying the comparison of clustering results across different K values. Clumpak incorporates additional features, such as implementations of methods for choosing K and comparing solutions obtained by different programs, models, or data subsets. Clumpak, available at http://clumpak.tau.ac.il, simplifies the use of model‐based analyses of population structure in population genetics and molecular ecology. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Molecular Ecology Resources Wiley

Clumpak: a program for identifying clustering modes and packaging population structure inferences across K

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References (69)

Publisher
Wiley
Copyright
Copyright © 2015 John Wiley & Sons Ltd
ISSN
1755-098X
eISSN
1755-0998
DOI
10.1111/1755-0998.12387
pmid
25684545
Publisher site
See Article on Publisher Site

Abstract

The identification of the genetic structure of populations from multilocus genotype data has become a central component of modern population‐genetic data analysis. Application of model‐based clustering programs often entails a number of steps, in which the user considers different modelling assumptions, compares results across different predetermined values of the number of assumed clusters (a parameter typically denoted K), examines multiple independent runs for each fixed value of K, and distinguishes among runs belonging to substantially distinct clustering solutions. Here, we present Clumpak (Cluster Markov Packager Across K), a method that automates the postprocessing of results of model‐based population structure analyses. For analysing multiple independent runs at a single K value, Clumpak identifies sets of highly similar runs, separating distinct groups of runs that represent distinct modes in the space of possible solutions. This procedure, which generates a consensus solution for each distinct mode, is performed by the use of a Markov clustering algorithm that relies on a similarity matrix between replicate runs, as computed by the software Clumpp. Next, Clumpak identifies an optimal alignment of inferred clusters across different values of K, extending a similar approach implemented for a fixed K in Clumpp and simplifying the comparison of clustering results across different K values. Clumpak incorporates additional features, such as implementations of methods for choosing K and comparing solutions obtained by different programs, models, or data subsets. Clumpak, available at http://clumpak.tau.ac.il, simplifies the use of model‐based analyses of population structure in population genetics and molecular ecology.

Journal

Molecular Ecology ResourcesWiley

Published: Jan 1, 2015

Keywords: ; ; ;

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