Hearn David, Huber Mark
Plant Sciences, University of Arizona, 303 Forbes Building, Tucson, AZ 85721, USA.
Syst Biol. 2006 Oct;55(5):803-17. doi: 10.1080/10635150600981562.
The ancestral distance test is introduced to detect correlated evolution between two binary traits in large phylogenies that may lack resolved subclades, branch lengths, and/or comparative data. We define the ancestral distance as the time separating a randomly sampled taxon from its most recent ancestor (MRA) with extant descendants that have an independent trait. The sampled taxon either has (target sample) or lacks (nontarget sample) a dependent trait. Modeled as a Markov process, we show that the distribution of ancestral distances for the target sample is identical to that of the nontarget sample when characters are uncorrelated, whereas ancestral distances are smaller on average for the target sample when characters are correlated. Simulations suggest that the ancestral distance can be estimated using the time, total branch length, taxonomic rank, or number of speciation events between a sampled taxon and the MRA. These results are shown to be robust to deviations from Markov assumptions. A Monte Carlo technique estimates P-values when fully resolved phylogenies with branch lengths are available, and we evaluate the Monte Carlo approach using a data set with known correlation. Measures of relatedness were found to provide a robust means to test hypotheses of correlated character evolution.
引入祖先距离检验以检测大型系统发育中两个二元性状之间的相关进化，这些系统发育可能缺乏解析的亚分支、分支长度和/或比较数据。我们将祖先距离定义为一个随机抽样的分类单元与其具有独立性状的现存后代的最近共同祖先（MRA）之间的时间间隔。抽样的分类单元具有（目标样本）或缺乏（非目标样本）一个相关性状。作为一个马尔可夫过程建模，我们表明当性状不相关时，目标样本的祖先距离分布与非目标样本的祖先距离分布相同，而当性状相关时，目标样本的祖先距离平均较小。模拟表明，可以使用抽样分类单元与MRA之间的时间、总分支长度、分类等级或物种形成事件数量来估计祖先距离。这些结果表明对偏离马尔可夫假设具有鲁棒性。当具有分支长度的完全解析系统发育可用时，蒙特卡罗技术估计P值，并且我们使用具有已知相关性的数据集评估蒙特卡罗方法。发现亲缘关系度量为检验相关性状进化的假设提供了一种鲁棒的方法。
