CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure
Author(s) -
Mattias Jakobsson,
Noah A. Rosenberg
Publication year - 2007
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btm233
Subject(s) - replicate , cluster analysis , permutation (music) , matching (statistics) , population , set (abstract data type) , cluster (spacecraft) , computer science , data mining , machine learning , artificial intelligence , statistics , mathematics , physics , demography , sociology , acoustics , programming language
Clustering of individuals into populations on the basis of multilocus genotypes is informative in a variety of settings. In population-genetic clustering algorithms, such as BAPS, STRUCTURE and TESS, individual multilocus genotypes are partitioned over a set of clusters, often using unsupervised approaches that involve stochastic simulation. As a result, replicate cluster analyses of the same data may produce several distinct solutions for estimated cluster membership coefficients, even though the same initial conditions were used. Major differences among clustering solutions have two main sources: (1) 'label switching' of clusters across replicates, caused by the arbitrary way in which clusters in an unsupervised analysis are labeled, and (2) 'genuine multimodality,' truly distinct solutions across replicates.
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