Lohse Konrad, Kelleher Jerome
Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK.
Genet Res (Camb). 2009 Aug;91(4):281-92. doi: 10.1017/S0016672309990139.
The degree of starshape of a genealogy is readily detectable using summary statistics and can be taken as a surrogate for the effect of past demography and other non-neutral forces. Summary statistics such as Tajima's D and related measures are commonly used for this. However, it is well known that because of their neglect of the genealogy underlying a sample such neutrality tests are far from ideal. Here, we investigate the properties of two types of summary statistics that are derived by considering the genealogy: (i) genealogical ratios based on the number of mutations on the rootward branches, which can be inferred from sequence data using a simple algorithm and (ii) summary statistics that use properties of a perfectly star-shaped genealogy. The power of these measures to detect a history of exponential growth is compared with that of standard summary statistics and a likelihood method for the single and multi-locus case. Statistics that depend on pairwise measures such as Tajima's D have comparatively low power, being sensitive to the random topology of the underlying genealogy. When analysing multi-locus data, we find that the genealogical measures are most powerful. Provided reliable outgroup information is available they may constitute a useful alternative to full likelihood estimation and standard tests of neutrality.
利用汇总统计量可以很容易地检测到一个谱系的星状程度，并且可以将其作为过去人口统计学和其他非中性力量影响的替代指标。诸如 Tajima's D 等汇总统计量及相关指标通常用于此目的。然而，众所周知，由于这些方法忽略了样本背后的谱系，因此这种中性检验远非理想。在此，我们研究了通过考虑谱系得出的两类汇总统计量的性质：（i）基于向根分支上突变数量的谱系比率，可使用简单算法从序列数据中推断得出；（ii）利用完美星状谱系性质的汇总统计量。将这些指标检测指数增长历史的能力与标准汇总统计量以及单基因座和多基因座情况下的似然方法进行了比较。依赖成对测量的统计量，如 Tajima's D，功效相对较低，对基础谱系的随机拓扑结构敏感。在分析多基因座数据时，我们发现谱系指标功效最强。如果有可靠的外类群信息，它们可能构成全似然估计和标准中性检验的有用替代方法。
