利用聚合阻滞剂推断种群历史：回顾与展望
Inference of Population History using Coalescent HMMs: Review and Outlook
摘要：
研究不同的人类种群是如何相关的是历史和人类学的兴趣，除了提供一个现实的空模型来测试自然选择或疾病协会的签名。此外，了解其他物种的人口统计历史在保护遗传学中发挥着越来越重要的作用。已经开发了许多统计方法来使用全基因组序列数据推断人口统计学历史，最近的进展集中在允许更灵活的建模选择，扩展到更大的数据集，并增加统计能力。在这里，我们回顾合并隐马尔可夫模型，一类强大的人口遗传推理方法，可以有效地利用连锁不平衡信息。我们强调最近的进展，为从业者提供建议，指出潜在的陷阱，并提出未来可能的研究方向。
英文摘要：
Studying how diverse human populations are related is of historical and anthropological interest, in addition to providing a realistic null model for testing for signatures of natural selection or disease associations. Furthermore, understanding the demographic histories of other species is playing an increasingly important role in conservation genetics. A number of statistical methods have been developed to infer population demographic histories using whole-genome sequence data, with recent advances focusing on allowing for more flexible modeling choices, scaling to larger data sets, and increasing statistical power. Here we review coalescent hidden Markov models, a powerful class of population genetic inference methods that can effectively utilize linkage disequilibrium information. We highlight recent advances, give advice for practitioners, point out potential pitfalls, and present possible future research directions.
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