Ancestral processes with selection
Ancestral processes with selection
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DOI：
10.1006/tpbi.1997.1299
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发表时间：
1997-06-01
影响因子：
1.4
通讯作者：
Neuhauser, C
中科院分区：
文献类型：
--
作者：
Krone, SM;Neuhauser, C
在本文中，我们展示了如何通过选择和突变的一大类模型构建基因样本的谱系。每个基因对应于一个不存在重组的基因座。样本的谱系嵌入在我们称为祖先选择图的图中。该图包含有关祖先的所有信息；它类似于在没有选择的情况下出现的金曼合并过程。祖先选择图可以很容易地模拟，我们概述了一种用于模拟样本的算法。主要目标是分析祖先选择图并将其与金曼的合并过程进行比较。在没有突变的情况下，我们发现到最近共同祖先的时间分布不依赖于选择系数，因此与中性情况下相同。当突变率为正时，我们给出了一个计算样本中两个个体通过血统和时间拉普拉斯变换到两个个体样本的最近共同祖先相同的概率的过程；我们根据选择系数评估它们各自幂级数的前两项。血统同一性的概率取决于选择系数和突变大鼠，并且与中性情况下的类似表达不同。拉普拉斯变换在选择系数中没有线性校正项，Vile 还提供了一个递归公式，可以通过沿着祖先选择图的样本路径向后模拟来近似给定样本的概率，这是由 Griffiths 和 Tavare (1994) 开发的技术。 (C) 1997 年学术出版社。
In this paper, we show how to construct the genealogy of a sample of genes far a large class of models with selection and mutation. Each gene corresponds to a single locus at which there is no recombination. The genealogy of the sample is embedded in a graph which we call the ancestral selection graph. This graph contains all the information about the ancestry; it is the analogue of Kingman's coalescent process which arises in the case with no selection. The ancestral selection graph can be easily simulated and we outline an algorithm for simulating samples. The main goal is to analyze the ancestral selection graph and to compare it to Kingman's coalescent process. In the case of no mutation, we find that the distribution of the time to the most recent common ancestor does not depend on the selection coefficient and hence is the same as in the neutral case. When the mutation rate is positive, we give a procedure for computing the probability that two individuals in a sample are identical by descent and the Laplace transform of the time to the most recent common ancestor of a sample of two individuals; we evaluate the first two terms of their respective power series in terms of the selection coefficient. The probability of identity by descent depends on both the selection coefficient and the mutation rats and is different from the analogous expression ire the neutral case. The Laplace transform does not have a linear correction term in the selection coefficient, Vile also provide a recursion formula that can be used to approximate the probability of a given sample by simulating backwards along the sample paths of the ancestral selection graph, a technique developed by Griffiths and Tavare (1994). (C) 1997 Academia Press.