ArticleMolecular biology and evolution2012
Model averaging and Bayes factor calculation of relaxed molecular clocks in Bayesian phylogenetics.
Article in Molecular biology and evolution, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
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52 citing papers in PubMed.
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- Analysis of the Entire Mitogenome of the Threatened Freshwater StingrayInternational journal of molecular sciences · 2025Article
- Modeling Substitution Rate Evolution across Lineages and Relaxing the Molecular Clock.Genome biology and evolution · 2024Review
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- Contrasting dynamics of two incursions of low-pathogenicity avian influenza virus into Australia.Virus evolution · 2024Article
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- Detecting Episodic Evolution through Bayesian Inference of Molecular Clock Models.Molecular biology and evolution · 2023Article
- Australia as a global sink for the genetic diversity of avian influenza A virus.PLoS pathogens · 2022Article
- Chilli leaf curl disease populations in India are highly recombinant, and rapidly segregated.3 Biotech · 2022Article
- Evolutionary features of a prolific subtype of avian influenza A virus in European waterfowl.Virus evolution · 2022Article
- Evolutionary Dynamics of Type 2 Porcine Reproductive and Respiratory Syndrome Virus by Whole-Genome Analysis.Viruses · 2021Article
- Trends and Intensity of Rhinovirus Invasions in Kilifi, Coastal Kenya, Over a 12-Year Period, 2007-2018.Open forum infectious diseases · 2021Article
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2 authors.
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Abstract
We describe a procedure for model averaging of relaxed molecular clock models in Bayesian phylogenetics. Our approach allows us to model the distribution of rates of substitution across branches, averaged over a set of models, rather than conditioned on a single model. We implement this procedure and test it on simulated data to show that our method can accurately recover the true underlying distribution of rates. We applied the method to a set of alignments taken from a data set of 12 mammalian species and uncovered evidence that lognormally distributed rates better describe this data set than do exponentially distributed rates. Additionally, our implementation of model averaging permits accurate calculation of the Bayes factor(s) between two or more relaxed molecular clock models. Finally, we introduce a new computational approach for sampling rates of substitution across branches that improves the convergence of our Markov chain Monte Carlo algorithms in this context. Our methods are implemented under the BEAST 1.6 software package, available at http://beast-mcmc.googlecode.com.
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