The Effects of Rate Variation on Ancestral Inference in the Coalescent

Corresponding author: Simon Tavaré, Program in Molecular Biology, Department of Biological Sciences, SHS 172, 835 W. 37th St., University of Southern California, Los Angeles, CA 90089-1340., stavare{at}gnome.usc.edu (E-mail)

Communicating editor: G. A. CHURCHILL

We describe a Markov chain Monte Carlo approach for assessing the role of site-to-site rate variation in the analysis of within-population samples of DNA sequences using the coalescent. Our framework is a Bayesian one. We discuss methods for assessing the goodness-of-fit of these models, as well as problems concerning the separate estimation of effective population size and mutation rate. Using a mitochondrial data set for illustration, we show that ancestral inference concerning coalescence times can be dramatically affected if rate variation is ignored.

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