| Literature DB >> 36083441 |
Abstract
This protocol explains how to use the program MCMCtree to estimate divergence times in microbial phylogenies. The main advantage of MCMCtree is the implementation of an approximation to the molecular data likelihood that dramatically speeds up computation during Bayesian MCMC sampling of divergence times and evolutionary rates. The approximation allows the analysis of large phylogenies with hundreds of taxa and molecular alignments with thousands or millions of sites. Two examples are used to illustrate Bayesian clock dating with MCMCtree. The first is a phylogeny of (mostly) microbial eukaryotes and prokaryotes encompassing the major groups of life on Earth, and for which fossil information, to calibrate the nodes of the phylogeny, is available. The second is a phylogeny of influenza viruses with known sampling times. An overview of Bayesian MCMC sampling is given as well as practical advice on issues such as construction of the time and rate prior and assessment of convergence of MCMC chains. Strategies for estimating times in microbial phylogenies for which neither fossil information nor sampling times are known are discussed.Entities:
Keywords: Bayesian method; Eukaryote; Fossil record; Influenza; Likelihood approximation; Molecular clock; Phylogeny; Prokaryote
Mesh：
Year: 2022 PMID： 36083441 DOI： 10.1007/978-1-0716-2691-7_1
Source DB: PubMed Journal: Methods Mol Biol ISSN： 1064-3745