Journal article
A biologist's guide to Bayesian phylogenetic analysis
- Abstract:
- Bayesian methods have become very popular in molecular phylogenetics due to the availability of user-friendly software implementing sophisticated models of evolution. However, Bayesian phylogenetic models are complex, and analyses are often carried out using default settings, which may not be appropriate. Here, we summarize the major features of Bayesian phylogenetic inference and discuss Bayesian computation using Markov chain Monte Carlo (MCMC), the diagnosis of an MCMC run, and ways of summarising the MCMC sample. We discuss the specification of the prior, the choice of the substitution model, and partitioning of the data. Finally, we provide a list of common Bayesian phylogenetic software and provide recommendations as to their use.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Access Document
- Files:
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(Preview, Accepted manuscript, pdf, 1.1MB, Terms of use)
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- Publisher copy:
- 10.1038/s41559-017-0280-x
Authors
- Publisher:
- Nature Publishing Group
- Journal:
- Nature Ecology and Evolution More from this journal
- Volume:
- 1
- Issue:
- 2017
- Pages:
- 1446-1454
- Publication date:
- 2017-09-21
- Acceptance date:
- 2017-07-17
- DOI:
- ISSN:
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2397-334X
- Pubs id:
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pubs:809763
- UUID:
-
uuid:3681d271-ddd3-4051-a749-cccf7a7bcb44
- Local pid:
-
pubs:809763
- Source identifiers:
-
809763
- Deposit date:
-
2017-12-07
Terms of use
- Copyright holder:
- © Nascimento, dos Reis, and Yang, 2017
- Copyright date:
- 2017
- Notes:
- This is the author accepted manuscript following peer review version of the article. The final version is available online from Nature Publishing Group at: 10.1038/s41559-017-0280-x
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