Kuhner M K, Yamato J, Felsenstein J
Department of Genetics, University of Washington, Seattle 98195-7360, USA.
Genetics. 1995 Aug;140(4):1421-30. doi: 10.1093/genetics/140.4.1421.
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.
我们提出了一种基于分子序列的群体样本对参数4Nμ（有效群体大小乘以每个位点的突变率，即θ）进行最大似然估计的新方法。我们使用Metropolis-Hastings马尔可夫链蒙特卡罗方法，以与它们相对于数据的似然性和相对于合并分布的先验概率的乘积成比例的方式对谱系进行采样。必须选择一个特定的θ值来生成合并分布，但生成的树可用于评估其他θ值下的似然性，从而生成似然曲线。该过程将采样集中在那些贡献大部分似然性的谱系上，从而能够基于相对较小的样本估计有意义的似然曲线。该方法有可能扩展到涉及群体大小变化、重组和迁移的情况。
