Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data
Molecular sequences obtained at different sampling times from populations of rapidly
evolving pathogens and from ancient subfossil and fossil sources are increasingly available
with modern sequencing technology. Here, we present a Bayesian statistical inference
approach to the joint estimation of mutation rate and population size that incorporates the
uncertainty in the genealogy of such temporally spaced sequences by using Markov chain
Monte Carlo (MCMC) integration. The Kingman coalescent model is used to describe the …
evolving pathogens and from ancient subfossil and fossil sources are increasingly available
with modern sequencing technology. Here, we present a Bayesian statistical inference
approach to the joint estimation of mutation rate and population size that incorporates the
uncertainty in the genealogy of such temporally spaced sequences by using Markov chain
Monte Carlo (MCMC) integration. The Kingman coalescent model is used to describe the …
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