Testing a molecular clock without an outgroup: derivations of induced priors on branch-length restrictions in a Bayesian framework.
We propose a Bayesian method for testing molecular clock hypotheses for use with aligned sequence data from multiple taxa. Our method utilizes a nonreversible nucleotide substitution model to avoid the necessity of specifying either a known tree relating the taxa or an outgroup for rooting the tree. We employ reversible jump Markov chain Monte Carlo to sample from the posterior distribution of the phylogenetic model parameters and conduct hypothesis testing using Bayes factors, the ratio of the posterior to prior odds of competing models. Here, the Bayes factors reflect the relative support of the sequence data for equal rates of evolutionary change between taxa versus unequal rates, averaged over all possible phylogenetic parameters, including the tree and root position. As the molecular clock model is a restriction of the more general unequal rates model, we use the Savage-Dickey ratio to estimate the Bayes factors. The Savage-Dickey ratio provides a convenient approach to calculating Bayes factors in favor of sharp hypotheses. Critical to calculating the Savage-Dickey ratio is a determination of the prior induced on the modeling restrictions. We demonstrate our method on a well-studied mtDNA sequence data set consisting of nine primates. We find strong support against a global molecular clock, but do find support for a local clock among the anthropoids. We provide mathematical derivations of the induced priors on branch length restrictions assuming equally likely trees. These derivations also have more general applicability to the examination of prior assumptions in Bayesian phylogenetics.
Suchard
Marc A
MA
Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, California 90095-1766, USA.
Weiss
Robert E
RE
Sinsheimer
Janet S
JS
D000818:Animals; D001499:Bayes Theorem; D004272:DNA, Mitochondrial / Q000235:genetics; D003627:Data Interpretation, Statistical; D019143:Evolution, Molecular; D015233:Models, Statistical; D009010:Monte Carlo Method; D009154:Mutation / Q000235:genetics*; D010802:Phylogeny; D011323:Primates / Q000235:genetics
D004272:DNA, Mitochondrial