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The distribution of Fst and other genetic statistics for a class of population structure models

机译:一类人口结构模型的F st 分布和其他遗传统计

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We examine genetic statistics used in the study of structured populations. In a 1999 paper, Wakeley observed that the coalescent process associated with the finite island model can be decomposed into a scattering phase and a collecting phase. This decomposition becomes exact in the large population limit with the coalescent at the end of the scattering phase converging to the Ewens sampling formula and the coalescent during the collecting phase converging to the Kingman coalescent. In this paper we introduce a class of limiting models, which we refer to as G/KC models, that generalize Wakeley’s decomposition. G in G/KC represents a completely general limit for the scattering phase, while KC represents a Kingman coalescent limit for the collecting phase. We show that both the island and two-dimensional stepping stone models converge to G/KC models in the large population limit. We then derive the distribution of the statistic F st for all G/KC models under a large sample limit for the cases of strong or weak mutation, thereby deriving the large population, large sample limiting distribution of F st for the island and two-dimensional stepping stone models as a special case of a general formula. Our methods allow us to take the large population and large sample limits simultaneously. In the context of large population, large sample limits, we show that the variance of F st in the presence of weak mutation collapses as O(frac1logd){O(frac{1}{log d})} where d is the number of demes sampled. Further, we show that this O(frac1logd){O(frac{1}{log d})} is caused by a heavy tail in the distribution of F st . Our analysis of F st can be extended to an entire class of genetic statistics, and we use our approach to examine homozygosity measures. Our analysis uses coalescent based methods.
机译:我们检查用于结构化人口研究的遗传统计。 Wakeley在1999年的一篇论文中观察到,与有限岛模型相关的合并过程可以分解为散射阶段和收集阶段。在较大的人口限制下,这种分解变得精确,散射阶段结束时的聚结会聚到Ewens采样公式,而收集阶段的聚结会聚到Kingman聚结。在本文中,我们介绍了一类限制模型,我们将其称为G / KC模型,该模型推广了Wakeley的分解。 G / KC中的G代表散射阶段的完全通用极限,而KC代表收集阶段的Kingman聚结极限。我们显示,在人口众多的情况下,岛屿模型和二维垫脚石模型都收敛于G / KC模型。然后,我们得出在强或弱突变情况下,在大样本限制下所有G / KC模型的统计量F st 的分布,从而得出F < sub> st 用于岛屿和二维垫脚石模型,作为一般公式的特例。我们的方法使我们能够同时处理大量样本和大量样本。在人口众多,样本量较大的情况下,我们表明在存在弱突变的情况下F st 的方差随着O(frac1logd){O(frac {1} {log d})而崩溃}其中d是采样的采样数。此外,我们表明此O(frac1logd){O(frac {1} {log d})}是由F st 的分布中的一条重尾引起的。我们对F st 的分析可以扩展到整个遗传统计类别,并且我们使用我们的方法来检查纯合度度量。我们的分析使用基于合并的方法。

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