Relative apparent synapomorphy analysis (RASA). I: The statistical measurement of phylogenetic signal

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 metho...

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Bibliographic Details
Published in:Molecular biology and evolution 1996-07, Vol.13 (6), p.749-757
Main Authors: Lyons-Weiler, J, Hoelzer, G A, Tausch, R J
Format: Article
Language:English
Subjects:
Algorithms
Bacteriophage T7 - genetics
Bacteriophage T7 - ultrastructure
Computer Simulation
Evolution, Molecular
Models, Genetic
phage T7
Phenotype
Phylogeny
Software
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Summary: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.
ISSN:0737-4038
1537-1719
DOI:10.1093/oxfordjournals.molbev.a025635