Huelsenbeck John P, Rannala Bruce
Section of Ecology, Behavior and Evolution, Division of Biological Sciences, University of California, San Diego, La Jolla, California 92093-0116, USA.
Evolution. 2003 Jun;57(6):1237-47. doi: 10.1111/j.0014-3820.2003.tb00332.x.
The importance of accommodating the phylogenetic history of a group when performing a comparative analysis is now widely recognized. The typical approaches either assume the tree is known without error, or they base inferences on a collection of well-supported trees or on a collection of trees generated under a stochastic model of cladogenesis. However, these approaches do not adequately account for the uncertainty of phylogenetic trees in a comparative analysis, especially when data relevant to the phylogeny of a group are available. Here, we develop a method for performing comparative analyses that is based on an extension of Felsenstein's independent contrasts method. Uncertainties in the phylogeny, branch lengths, and other parameters are accommodated by averaging over all possible trees, weighting each by the probability that the tree is correct. We do this in a Bayesian framework and use Markov chain Monte Carlo to perform the high-dimensional summations and integrations required by the analysis. We illustrate the method using comparative characters sampled from Anolis lizards.
在进行比较分析时考虑一个类群的系统发育历史的重要性现在已得到广泛认可。典型的方法要么假定树是已知且无误差的,要么基于一组得到充分支持的树或基于在分支发生的随机模型下生成的一组树进行推断。然而,这些方法在比较分析中没有充分考虑系统发育树的不确定性,特别是当与一个类群的系统发育相关的数据可用时。在这里,我们开发了一种基于费尔斯滕森独立对比方法扩展的比较分析方法。通过对所有可能的树进行平均,并根据树正确的概率对每棵树进行加权,来考虑系统发育、分支长度和其他参数的不确定性。我们在贝叶斯框架下进行此操作,并使用马尔可夫链蒙特卡罗方法来执行分析所需的高维求和与积分。我们使用从安乐蜥采样的比较特征来说明该方法。