A popular approach to learning about admixture from population genetic data is by computing the allele‐sharing summary statistics known as f‐statistics. Compared to some methods in population genetics, f‐statistics are relatively simple, but interpreting them can still be complicated at times. In addition, f‐statistics can be used to build admixture graphs (multi‐population trees allowing for admixture events), which provide more explicit and thorough modelling capabilities but are correspondingly more complex to work with. Here, I discuss some of these issues to provide users of these tools with a basic guide for protocols and procedures. My focus is on the kinds of conclusions that can or cannot be drawn from the results of f₄‐statistics and admixture graphs, illustrated with real‐world examples involving human populations.

中文翻译：

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应用 f4 统计量和混合图：理论和示例。

从种群遗传数据中了解混合的一种流行方法是计算称为f统计量的等位基因共享汇总统计量。与群体遗传学中的一些方法相比，f-统计量相对简单，但有时解释它们仍然很复杂。此外，f- statistics 可用于构建混合图（允许混合事件的多种群树），它提供更明确和全面的建模能力，但相应地使用起来更复杂。在这里，我将讨论其中一些问题，以便为这些工具的用户提供协议和程序的基本指南。我的重点是可以或不能从f ₄的结果中得出的结论类型- 统计数据和混合图，以涉及人口的真实世界示例进行说明。