Maximum Likelihood Estimation of Recombination Rates From Population Data

Abstract

Abstract We describe a method for co-estimating r = C/μ (where C is the per-site recombination rate and μ is the per-site neutral mutation rate) and Θ = 4Neμ (where Ne is the effective population size) from a population sample of molecular data. The technique is Metropolis-Hastings sampling: we explore a large number of possible reconstructions of the recombinant genealogy, weighting according to their posterior probability with regard to the data and working values of the parameters. Different relative rates of recombination at different locations can be accommodated if they are known from external evidence, but the algorithm cannot itself estimate rate differences. The estimates of Θ are accurate and apparently unbiased for a wide range of parameter values. However, when both Θ and r are relatively low, very long sequences are needed to estimate r accurately, and the estimates tend to be biased upward. We apply this method to data from the human lipoprotein lipase locus.