Open AccessMaximum Likelihood Estimation of Recombination Rates From Population Data
Author(s) -
Mary K. Kuhner,
Jon Yamato,
Joseph Felsenstein
Publication year - 2000
Publication title -
genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.792
H-Index - 246
eISSN - 1943-2631
pISSN - 0016-6731
DOI - 10.1093/genetics/156.3.1393
Subject(s) - recombination rate , recombination , weighting , biology , statistics , population , mutation rate , sampling (signal processing) , locus (genetics) , range (aeronautics) , sampling bias , genetics , mathematics , sample size determination , computer science , demography , physics , gene , materials science , filter (signal processing) , sociology , acoustics , composite material , computer vision
We describe a method for co-estimating r = C/mu (where C is the per-site recombination rate and mu is the per-site neutral mutation rate) and Theta = 4N(e)mu (where N(e) 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 Theta are accurate and apparently unbiased for a wide range of parameter values. However, when both Theta 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.