Estimating effective population size and mutation rate from sequence data using Metropolis-Hastings sampling.
Year: 1995
Type: article
Abstract: We present a new way to make a maximum likelihood estimate of the parameter 4N mu (effective population size times mutation rate per site, or theta) based on a population sample of molecular sequences. We use a Metropolis-Hastings Markov chain Monte Carlo method to sample genealogies in proportion to the product of their likelihood with respect to the data and their prior probability with respect to a coalescent distribution. A specific value of theta must be chosen to generate the coalescent distribution, but the resulting trees can be used to evaluate the likelihood at other values of theta, generating a likelihood curve. This procedure concentrates sampling on those genealogies that contribute most of the likelihood, allowing estimation of meaningful likelihood curves based on relatively small samples. The method can potentially be extended to cases involving varying population size, recombination, and migration.
Source: Genetics
Authors: M K Kuhner, J Yamato, J Felsenstein
Institution: University of Washington
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2124061807