Bayesian random local clocks, or one rate to rule them all

• Main Authors: Drummond Alexei J, Suchard Marc A
• Format: Article
• Language: English
• Published: BMC 2010-08-01
• Series: BMC Biology
• Online Access: http://www.biomedcentral.com/1741-7007/8/114

<p>Abstract</p> <p>Background</p> <p>Relaxed molecular clock models allow divergence time dating and "relaxed phylogenetic" inference, in which a time tree is estimated in the face of unequal rates across lineages. We present a new method for relaxing the assumption of a strict molecular clock using Markov chain Monte Carlo to implement Bayesian modeling averaging over random local molecular clocks. The new method approaches the problem of rate variation among lineages by proposing a series of local molecular clocks, each extending over a subregion of the full phylogeny. Each branch in a phylogeny (subtending a clade) is a possible location for a change of rate from one local clock to a new one. Thus, including both the global molecular clock and the unconstrained model results, there are a total of 2^{2<it>n-</it>2}possible rate models available for averaging with 1, 2, ..., 2<it>n - </it>2 different rate categories.</p> <p>Results</p> <p>We propose an efficient method to sample this model space while simultaneously estimating the phylogeny. The new method conveniently allows a direct test of the strict molecular clock, in which one rate rules them all, against a large array of alternative local molecular clock models. We illustrate the method's utility on three example data sets involving mammal, primate and influenza evolution. Finally, we explore methods to visualize the complex posterior distribution that results from inference under such models.</p> <p>Conclusions</p> <p>The examples suggest that large sequence datasets may only require a small number of local molecular clocks to reconcile their branch lengths with a time scale. All of the analyses described here are implemented in the open access software package BEAST 1.5.4 (<url>http://beast-mcmc.googlecode.com/</url>).</p>