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Phylogeographical analyses have become commonplace for a myriad of organisms with the advent of cheap DNA sequencing technologies. Bayesian model-based clustering is a powerful tool for detecting important patterns in such data and can be used to decipher even quite subtle signals of systematic differences in molecular variation. Here, we introduce two upgrades to the Bayesian Analysis of Population Structure (BAPS) software, which enable 1) spatially explicit modeling of variation in DNA sequences and 2) hierarchical clustering of DNA sequence data to reveal nested genetic population structures. We provide a direct interface to map the results from spatial clustering with Google Maps using the portal http://www.spatialepidemiology.net/ and illustrate this approach using sequence data from Borrelia burgdorferi. The usefulness of hierarchical clustering is demonstrated through an analysis of the metapopulation structure within a bacterial population experiencing a high level of local horizontal gene transfer. The tools that are introduced are freely available at http://www.helsinki.fi/bsg/software/BAPS/.

Original publication

DOI

10.1093/molbev/mst028

Type

Journal article

Journal

Molecular biology and evolution

Publication Date

05/2013

Volume

30

Pages

1224 - 1228

Addresses

Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland.

Keywords

Borrelia burgdorferi, Bayes Theorem, Sequence Analysis, DNA, Genetics, Population, Evolution, Molecular, Software