A NEW PHYLOGENETIC METHOD FOR IDENTIFYING EXCEPTIONAL PHENOTYPIC DIVERSIFICATION
A NEW PHYLOGENETIC METHOD FOR IDENTIFYING EXCEPTIONAL PHENOTYPIC DIVERSIFICATION
复制标题
一种识别异常表型多样性的新系统发育方法
DOI：
10.1111/j.1558-5646.2011.01435.x
复制
发表时间：
2012
期刊：
影响因子：
3.3
通讯作者：
B. Redelings
中科院分区：
文献类型：
--
作者：
L. Revell;D. Mahler;P. Peres‐Neto;B. Redelings
目前可用的系统发育方法，用于研究在一个连续值的字符的进化速率假设，该速率是恒定的整个树或它改变沿着特定的分支根据一个先验假设的速率变化由用户提供。在这里，我们描述了一种新的方法来研究进化速率变化的连续值字符的物种在我们的研究中的系统发育历史的估计。根据这种方法，我们没有提出具体的先验假设，在我们的研究中，进化速率的变化是如何在整个物种的历史结构。相反，我们使用贝叶斯马尔可夫链蒙特卡罗方法来估计进化速率和树上速率之间的转换点。我们通过同时采样率和移位点与其后验概率成比例来实现这一点，然后将后验样本折叠成感兴趣参数的估计。我们使用模拟表明，该方法是相当成功的，在确定进化速度的转变的系统发育位置，估计的速率是渐近无偏的。我们还提供了一个经验的例子，该方法使用的数据Anolis蜥蜴。
Currently available phylogenetic methods for studying the rate of evolution in a continuously valued character assume that the rate is constant throughout the tree or that it changes along specific branches according to an a priori hypothesis of rate variation provided by the user. Herein, we describe a new method for studying evolutionary rate variation in continuously valued characters given an estimate of the phylogenetic history of the species in our study. According to this method, we propose no specific prior hypothesis for how the variation in evolutionary rate is structured throughout the history of the species in our study. Instead, we use a Bayesian Markov Chain Monte Carlo approach to estimate evolutionary rates and the shift point between rates on the tree. We do this by simultaneously sampling rates and shift points in proportion to their posterior probability, and then collapsing the posterior sample into an estimate of the parameters of interest. We use simulation to show that the method is quite successful at identifying the phylogenetic position of a shift in the rate of evolution, and that estimated rates are asymptotically unbiased. We also provide an empirical example of the method using data for Anolis lizards.