UCL logo

UCL Discovery

UCL home » Library Services » Electronic resources » UCL Discovery

A Bayesian approach to phylogeographic clustering.

Manolopoulou, I; Legarreta, L; Emerson, BC; Brooks, S; Tavaré, S; (2011) A Bayesian approach to phylogeographic clustering. Interface Focus , 1 (6) pp. 909-921. 10.1098/rsfs.2011.0054.

Full text not available from this repository.


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.

Type: Article
Title: A Bayesian approach to phylogeographic clustering.
Location: England
DOI: 10.1098/rsfs.2011.0054
Keywords: Markov chain Monte Carlo, coalescent, island model, migration, reversible jump, subdivided population
UCL classification: UCL > School of BEAMS
UCL > School of BEAMS > Faculty of Maths and Physical Sciences
URI: http://discovery.ucl.ac.uk/id/eprint/1361666
Downloads since deposit
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item