Kuhner M K, Yamato J, Felsenstein J
Department of Genetics, University of Washington, Seattle, Washington 98195, USA.
Genetics. 2000 Nov;156(3):1393-401. doi: 10.1093/genetics/156.3.1393.
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.
我们描述了一种从分子数据的群体样本中共同估计r = C/mu(其中C是每一位点的重组率,mu是每一位点的中性突变率)和Theta = 4N(e)mu(其中N(e)是有效群体大小)的方法。该技术是Metropolis-Hastings抽样:我们探索大量重组谱系的可能重构,根据它们相对于数据和参数工作值的后验概率进行加权。如果从外部证据已知不同位置的不同相对重组率,则可以考虑这些情况,但该算法本身无法估计速率差异。对于广泛的参数值,Theta的估计是准确的且显然无偏差。然而,当Theta和r都相对较低时,需要非常长的序列才能准确估计r,并且估计往往会向上偏倚。我们将此方法应用于来自人类脂蛋白脂肪酶基因座的数据。