A Bayesian approach to modelling reticulation events with application to the ribosomal protein gene rps11 of flowering plants
Radice, Rosalba (2012) A Bayesian approach to modelling reticulation events with application to the ribosomal protein gene rps11 of flowering plants. Australian and New Zealand Journal of Statistics 54 (4), pp. 401-426. ISSN 1467-842X.
Abstract
Traditional phylogenetic inference assumes that the history of a set of taxa can be explained by a tree. This assumption is often violated as some biological entities can exchange genetic material giving rise to non-treelike events often called reticulations. Failure to consider these events might result in incorrectly inferred phylogenies. Phylogenetic networks provide a flexible tool which allows researchers to model the evolutionary history of a set of organisms in the presence of reticulation events. In recent years, a number of methods addressing phylogenetic network parameter estimation have been introduced. Some of them are based on the idea that a phylogenetic network can be defined as a directed acyclic graph. Based on this definition, we propose a Bayesian approach to the estimation of phylogenetic network parameters which allows for different phylogenies to be inferred at different parts of a multiple DNA alignment. The algorithm is tested on simulated data and applied to the ribosomal protein gene rps11 data from five flowering plants, where reticulation events are suspected to be present. The proposed approach can be applied to a wide variety of problems which aim at exploring the possibility of reticulation events in the history of a set of taxa.
Metadata
| Item Type: | Article |
|---|---|
| Keyword(s) / Subject(s): | Bayesian analysis, Markov chain, Monte Carlo, network, phylogenetics, reticulation event |
| School: | Birkbeck Faculties and Schools > Faculty of Business and Law > Birkbeck Business School |
| Depositing User: | Sarah Hall |
| Date Deposited: | 15 Apr 2014 13:47 |
| Last Modified: | 02 Aug 2023 17:10 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/9609 |
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