The detection of introgression from genomic data is transforming our view of species and the origins of adaptive variation. Among the most widely used approaches to detect introgression is the so-called ABBA BABA test or D statistic, which identifies excess allele sharing between non-sister taxa. Part of the appeal of D is its simplicity, but this also limits its informativeness, particularly about the timing and direction of introgression. Here we present a simple extension, D frequency spectrum or D_FS, in which D is partitioned according to the frequencies of derived alleles. We use simulations over a large parameter space to show how D_FS carries information about various factors. In particular, recent introgression reliably leads to a peak in D_FS among low-frequency derived alleles, whereas violation of model assumptions can lead to a lack of signal at low frequencies. We also reanalyse published empirical data from six different animal and plant taxa, and interpret the results in the light of our simulations, showing how D_FS provides novel insights. We currently see D_FS as a descriptive tool that will augment both simple and sophisticated tests for introgression, but in the future it may be usefully incorporated into probabilistic inference frameworks.University Research Fellowship

中文翻译：

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等位基因频谱渗入的特征。

从基因组数据检测渗入正在改变我们对物种和适应性变异起源的看法。用来检测基因渗入的最广泛使用的方法是所谓的ABBA BABA检验或D统计量，它可以识别非姐妹类群之间过量的等位基因共享。D的吸引力在于它的简单性，但这也限制了它的信息量，尤其是渗入的时间和方向。在这里，我们提出一个简单的扩展名D频谱或D _FS，其中D根据派生的等位基因的频率进行划分。我们在较大的参数空间上使用模拟来显示D _FS携带有关各种因素的信息。特别是，最近的基因渗入可靠地导致了低频衍生的等位基因中D _FS的峰值，而违反模型假设可能会导致低频信号不足。我们还重新分析了来自六个不同动植物类别的已发布经验数据，并根据我们的模拟解释了结果，从而显示了D _FS如何提供新颖的见解。目前，我们将D _FS视为一种描述性工具，它将增强对渗入的简单测试和复杂测试，但在将来可能会有用地将其纳入概率推断框架中。