Cyran Krzysztof A, Kimmel Marek
Institute of Informatics, Silesian University of Technology, Gliwice, Poland.
Theor Popul Biol. 2010 Nov;78(3):165-72. doi: 10.1016/j.tpb.2010.06.001. Epub 2010 Jun 19.
Methods of calculating the distributions of the time to coalescence depend on the underlying model of population demography. In particular, the models assuming deterministic evolution of population size may not be applicable to populations evolving stochastically. Therefore the study of coalescence models involving stochastic demography is important for applications. One interesting approach which includes stochasticity is the O'Connell limit theory of genealogy in branching processes. Our paper explores how many generations are needed for the limiting distributions of O'Connell to become adequate approximations of exact distributions. We perform extensive simulations of slightly supercritical branching processes and compare the results to the O'Connell limits. Coalescent computations under the Wright-Fisher model are compared with limiting O'Connell results and with full genealogy-based predictions. These results are used to estimate the age of the so-called mitochondrial Eve, i.e., the root of the mitochondrial polymorphisms of the modern humans based on the DNA from humans and Neanderthal fossils.
计算合并时间分布的方法取决于种群人口统计学的基础模型。特别是，假设种群大小确定性演化的模型可能不适用于随机演化的种群。因此，研究涉及随机人口统计学的合并模型对于实际应用很重要。一种包含随机性的有趣方法是分支过程中系谱的奥康奈尔极限理论。我们的论文探讨了奥康奈尔极限分布需要多少代才能成为精确分布的充分近似。我们对轻度超临界分支过程进行了广泛的模拟，并将结果与奥康奈尔极限进行比较。将赖特-费希尔模型下的合并计算与奥康奈尔极限结果以及基于完整系谱的预测进行比较。这些结果用于估计所谓线粒体夏娃的年代，即基于人类和尼安德特人化石的DNA的现代人类线粒体多态性的根源。
