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随机遗传漂变的 Wright-Fisher 模型、扩散逼近和中间模型的比较和内容。

Comparison and content of the Wright-Fisher model of random genetic drift, the diffusion approximation, and an intermediate model.

机构信息

Centre for Computational Systems Biology, Fudan University, Shanghai, People's Republic of China.

出版信息

J Theor Biol. 2011 Jan 21;269(1):79-87. doi: 10.1016/j.jtbi.2010.10.014. Epub 2010 Oct 19.

Abstract

We investigate the detailed connection between the Wright-Fisher model of random genetic drift and the diffusion approximation, under the assumption that selection and drift are weak and so cause small changes over a single generation. A representation of the mathematics underlying the Wright-Fisher model is introduced which allows the connection to be made with the corresponding mathematics underlying the diffusion approximation. Two 'hybrid' models are also introduced which lie 'between' the Wright-Fisher model and the diffusion approximation. In model 1 the relative allele frequency takes discrete values while time is continuous; in model 2 time is discrete and relative allele frequency is continuous. While both hybrid models appear to have a similar status and the same level of plausibility, the different nature of time and frequency in the two models leads to significant mathematical differences. Model 2 is mathematically inconsistent and has to be ruled out as being meaningful. Model 1 is used to clarify the content of Kimura's solution of the diffusion equation, which is shown to have the natural interpretation as describing only those populations where alleles are segregating. By contrast the Wright-Fisher model and the solution of the diffusion equation of McKane and Waxman cover populations of all categories, namely populations where alleles segregate, are lost, or fix.

摘要

我们研究了随机遗传漂变的 Wright-Fisher 模型与扩散近似之间的详细联系,假设选择和漂变较弱,因此在单个世代中只会引起小的变化。引入了 Wright-Fisher 模型的基础数学表示,使得可以与扩散近似的相应数学联系起来。还引入了两个“混合”模型,它们位于 Wright-Fisher 模型和扩散近似之间。在模型 1 中,相对等位基因频率取离散值,而时间是连续的;在模型 2 中,时间是离散的,而相对等位基因频率是连续的。虽然这两个混合模型似乎具有相似的地位和相同的可信度,但时间和频率在两个模型中的不同性质导致了显著的数学差异。模型 2 在数学上是不一致的,必须排除其有意义的可能性。模型 1 用于澄清 Kimura 对扩散方程的解的内容,该解被证明仅描述了那些等位基因正在分离的群体。相比之下,Wright-Fisher 模型和 McKane 和 Waxman 的扩散方程的解涵盖了所有类别的群体,即等位基因分离、丢失或固定的群体。

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