title: A dirichlet process prior for estimating lineage-specific substitution rates.
abstract: We introduce a new model for relaxing the assumption of a strict molecular clock for use as a prior in Bayesian methods for divergence time estimation. Lineage-specific rates of substitution are modeled using a Dirichlet process prior (DPP), a type of stochastic process that assumes lineages of a phylogenetic tree are distributed into distinct rate classes. Under the Dirichlet process, the number of rate classes, assignment of branches to rate classes, and the rate value associated with each class are treated as random variables. The performance of this model was evaluated by conducting analyses on data sets simulated under a range of different models. We compared the Dirichlet process model with two alternative models for rate variation: the strict molecular clock and the independent rates model. Our results show that divergence time estimation under the DPP provides robust estimates of node ages and branch rates without significantly reducing power. Further analyses were conducted on a biological data set, and we provide examples of ways to summarize Markov chain Monte Carlo samples under this model.
authors: Department of Ecology and Evolutionary Biology, University of Kansas, KS, USA. tracyh@berkeley.edu
authors: Tracy A
authors: TA
authors: Heath
authors: Mark T
authors: MT
authors: Holder
authors: John P
authors: JP
authors: Huelsenbeck
mesh_terms: D001499:Bayes Theorem; D003198:Computer Simulation; D019143:Evolution, Molecular; D008390:Markov Chains; D008957:Models, Genetic; D009010:Monte Carlo Method; D059645:Mutation Rate; D010802:Phylogeny; D013269:Stochastic Processes