Slatkin Montgomery
Department of Integrative Biology, University of California, Berkeley, CA 94720-3140, USA.
Curr Opin Genet Dev. 2016 Dec;41:72-76. doi: 10.1016/j.gde.2016.08.004. Epub 2016 Sep 5.
In the past few years, the number of autosomal DNA sequences from human fossils has grown explosively and numerous partial or complete sequences are available from our closest relatives, Neanderthal and Denisovans. I review commonly used statistical methods applied to these sequences. These methods fall into three broad classes: methods for estimating levels of contamination, descriptive methods, and methods based on population genetic models. The latter two classes are largely methods developed for the analysis of present-day genomic data. When they are applied to ancient DNA (aDNA), they usually ignore the time dimension. A few methods, particularly those concerned with inferring something about selection or ancestor-descendant relationships, take explicit account of the ages of aDNA samples.
在过去几年中,来自人类化石的常染色体DNA序列数量呈爆炸式增长,我们最近的亲属尼安德特人和丹尼索瓦人的许多部分或完整序列也已可得。我将回顾应用于这些序列的常用统计方法。这些方法大致可分为三大类:用于估计污染水平的方法、描述性方法以及基于群体遗传模型的方法。后两类方法主要是为分析现代基因组数据而开发的。当它们应用于古DNA(aDNA)时,通常忽略了时间维度。有一些方法,特别是那些与推断选择或祖先-后代关系有关的方法,明确考虑了aDNA样本的年代。