Ewing Greg, Rodrigo Allen
The Allan Wilson Centre for Molecular Ecology and Evolution, University of Auckland, Private Bag 920191, Auckland, New Zealand.
Mol Biol Evol. 2006 May;23(5):988-96. doi: 10.1093/molbev/msj111. Epub 2006 Feb 22.
We expand a coalescent-based method that uses serially sampled genetic data from a subdivided population to incorporate changes to the number of demes and patterns of colonization. Often, when estimating population parameters or other parameters of interest from genetic data, the demographic structure and parameters are not constant over evolutionary time. In this paper, we develop a Bayesian Markov chain Monte Carlo method that allows for step changes in mutation, migration, and population sizes, as well as changing numbers of demes, where the times of these changes are also estimated. We show that in parameter ranges of interest, reliable estimates can often be obtained, including the historical times of parameter changes. However, posterior densities of migration rates can be quite diffuse and estimators somewhat biased, as reported by other authors.
我们扩展了一种基于溯祖理论的方法，该方法利用来自细分群体的连续采样遗传数据，以纳入deme数量的变化和殖民模式。通常，当从遗传数据估计群体参数或其他感兴趣的参数时，人口结构和参数在进化时间内并非恒定不变。在本文中，我们开发了一种贝叶斯马尔可夫链蒙特卡罗方法，该方法允许突变、迁移和群体大小发生阶跃变化，以及deme数量发生变化，同时这些变化的时间也可被估计。我们表明，在感兴趣的参数范围内，通常可以获得可靠的估计值，包括参数变化的历史时间。然而，正如其他作者所报道的那样，迁移率的后验密度可能相当分散，估计值也会有一定偏差。
