title: Relative apparent synapomorphy analysis (RASA). I: The statistical measurement of phylogenetic signal.
abstract: 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.
authors: Graduate Program in Ecology, Evolution and Conservation Biology, University of Nevada, Reno 89512-0013, USA. weiler@grass.ers.unr.edu
authors: J
authors: J
authors: Lyons-Weiler
authors: G A
authors: GA
authors: Hoelzer
authors: R J
authors: RJ
authors: Tausch
mesh_terms: D000465:Algorithms; D017123:Bacteriophage T7 / Q000235:genetics / Q000648:ultrastructure; D003198:Computer Simulation; D019143:Evolution, Molecular; D008957:Models, Genetic; D010641:Phenotype; D010802:Phylogeny; D012984:Software