A Bayesian approach to phylogeographic clustering

Ioanna Manolopoulou, Lorenza Legarreta, Brent C. Emerson, Steve Brooks, Simon Tavaré

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)


Phylogeographic methods have attracted a lot of attention in recent years, stressing the need to provide a solid statistical framework for many existing methodologies so as to draw statistically reliable inferences. Here, we take a flexible fully Bayesian approach by reducing the problem to a clustering framework, whereby the population distribution can be explained by a set of migrations, forming geographically stable population clusters. These clusters are such that they are consistent with a fixed number of migrations on the corresponding (unknown) subdivided coalescent tree. Our methods rely upon a clustered population distribution, and allow for inclusion of various covariates (such as phenotype or climate information) at little additional computational cost. We illustrate our methods with an example from weevil mitochondrial DNA sequences from the Iberian peninsula.
Original languageEnglish
Pages (from-to)909-921
Number of pages13
JournalInterface Focus
Issue number6
Publication statusPublished - Dec 2011

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