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Genetics. Aug 1995; 140(4): 1421–1430.
PMCID: PMC1206705

Estimating Effective Population Size and Mutation Rate from Sequence Data Using Metropolis-Hastings Sampling


We present a new way to make a maximum likelihood estimate of the parameter 4N(e)μ (effective population size times mutation rate per site, or θ) 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 θ must be chosen to generate the coalescent distribution, but the resulting trees can be used to evaluate the likelihood at other values of θ, 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.

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Selected References

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  • Felsenstein J. Estimating effective population size from samples of sequences: inefficiency of pairwise and segregating sites as compared to phylogenetic estimates. Genet Res. 1992 Apr;59(2):139–147. [PubMed]
  • Kimura M. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol. 1980 Dec;16(2):111–120. [PubMed]
  • Ward RH, Frazier BL, Dew-Jager K, Päbo S. Extensive mitochondrial diversity within a single Amerindian tribe. Proc Natl Acad Sci U S A. 1991 Oct 1;88(19):8720–8724. [PMC free article] [PubMed]
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