| Inferring Evolutionary Rates Using Serially Sampled Sequences from Several Populations (2003) | |||||||||||||
Abstract | |||||||||||||
| The estimation of evolutionary rates from serially sampled sequences has recently been the focus of several studies. In this paper, we extend these analyses to allow the estimation of a joint rate of substitution, ω, from several evolving populations from which serial samples are drawn. In the case of viruses evolving in different hosts, therapy may halt replication and therefore the accumulation of substitutions in the population. In such cases, it may be that only a proportion, p, of subjects are non-responders who have viral populations that continue to evolve. We develop two likelihood-based procedures to jointly estimate p and ω, and empirical Bayes' tests of whether an individual should be classified as a responder or non-responder. An example dataset comprising HIV-1 partial envelope sequences from 6 patients on highly active antiretroviral therapy is analysed. | |||||||||||||
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