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Título: | A Bayesian approach to phylogeographic clustering |
Autor: | Manolopoulou, Ioanna; Legarreta, Lorenza; Emerson, Brent C. CSIC ORCID ; Brooks, Steve; Tavaré, Simon | Palabras clave: | Migration Subdivided population Reversible jump Island model Coalescent Markov chain Monte Carlo |
Fecha de publicación: | 31-ago-2011 | Editor: | Royal Society (Great Britain) | Citación: | Interface Focus 1(6): 909- 921 (2011) | Resumen: | 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. | Versión del editor: | http://dx.doi.org/10.1098/rsfs.2011.0054 | URI: | http://hdl.handle.net/10261/199615 | DOI: | 10.1098/rsfs.2011.0054 | Identificadores: | doi: 10.1098/rsfs.2011.0054 issn: 2042-8898 e-issn: 2042-8901 |
Aparece en las colecciones: | (IPNA) Artículos |
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