Methods to detect signals of natural selection from genomic data have traditionally emphasized the use of simple summary statistics. Here, we review a new generation of methods that consider combinations of conventional summary statistics and/or richer features derived from inferred gene trees and ancestral recombination graphs (ARGs). We also review recent advances in methods for population genetic simulation and ARG reconstruction. Finally, we describe opportunities for future work on a variety of related topics, including the genetics of speciation, estimation of selection coefficients, and inference of selection on polygenic traits. Together, these emerging methods offer promising new directions in the study of natural selection.

中文翻译：

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从汇总统计到基因树：推断正选择的方法。


从基因组数据中检测自然选择信号的方法传统上强调使用简单的汇总统计。在这里，我们回顾了新一代的方法，这些方法考虑了传统汇总统计数据和/或更丰富的特征的组合，这些特征源自推断的基因树和祖先重组图（ARG）。我们还回顾了群体遗传模拟和 ARG 重建方法的最新进展。最后，我们描述了未来在各种相关主题上开展工作的机会，包括物种形成遗传学、选择系数的估计以及多基因性状选择的推断。这些新兴方法共同为自然选择研究提供了有希望的新方向。