Lyons-Weiler J, Hoelzer G A, Tausch R J
Graduate Program in Ecology, Evolution and Conservation Biology, University of Nevada, Reno 89512-0013, USA.
Mol Biol Evol. 1996 Jul;13(6):749-57. doi: 10.1093/oxfordjournals.molbev.a025635.
We have developed a new approach to the measurement of phylogenetic signal in character state matrices called relative apparent synapomorphy analysis (RASA). RASA provides a deterministic, statistical measure of natural cladistic hierarchy (phylogenetic signal) in character state matrices. The method works by determining whether a measure of the rate of increase of cladistic similarity among pairs of taxa as a function of phenetic similarity is greater than a null equiprobable rate of increase. Our investigation of the utility and limitations of RASA using simulated and bacteriophage T7 data sets indicates that the method has numerous advantages over existing measures of signal. A first advantage is computational efficiency. A second advantage is that RASA employs known methods of statistical inference, providing measurable sensitivity and power. The performance of RASA is examined under various conditions of branching evolution as the number of characters, character states per character, and mutations per branch length are varied. RASA appears to provide an unbiased and reliable measure of phylogenetic signal, and the general approach promises to be useful in the development of new techniques that should increase the rigor and reliability of phylogenetic estimates.
我们开发了一种新方法来测量性状状态矩阵中的系统发育信号,称为相对表观共衍征分析(RASA)。RASA提供了一种对性状状态矩阵中自然分支层次结构(系统发育信号)的确定性统计测量。该方法通过确定作为表型相似性函数的类群对之间分支相似性增加率的测量是否大于零等概率增加率来起作用。我们使用模拟和噬菌体T7数据集对RASA的效用和局限性进行的研究表明,该方法相对于现有的信号测量方法具有许多优势。第一个优势是计算效率。第二个优势是RASA采用了已知的统计推断方法,提供了可测量的灵敏度和功效。随着字符数量、每个字符的字符状态以及每个分支长度的突变数量的变化,在分支进化的各种条件下检查了RASA的性能。RASA似乎提供了一种无偏且可靠的系统发育信号测量方法,并且这种一般方法有望在开发新技术中发挥作用,这些新技术应能提高系统发育估计的严谨性和可靠性。