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Parsimony, Phylogeny, and Genomics$
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Victor A. Albert

Print publication date: 2006

Print ISBN-13: 9780199297306

Published to Oxford Scholarship Online: September 2007

DOI: 10.1093/acprof:oso/9780199297306.001.0001

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Maximum parsimony and the phylogenetic information in multistate characters

Maximum parsimony and the phylogenetic information in multistate characters

(p.162) (p.163) Chapter 9 Maximum parsimony and the phylogenetic information in multistate characters
Parsimony, Phylogeny, and Genomics

Mike Steel

David Penny

Oxford University Press

This chapter investigates some of the statistical issues that surround the maximum parsimony method, for example, the question of statistical consistency. Other questions of interest include when will parsimony and likelihood select the same tree on any given data, and under what sort of model(s) is parsimony a likelihood method? This chapter describes some new sufficient conditions for such an equivalence, particularly as regards settings that involve a large state space. Traditionally, most of the biological studies involving maximum parsimony have involved a state space that is small and fixed. However, increasingly there is interest in genomic characters such as gene order, where the underlying state space may be large, and where it is likely that resulting states are unique evolutionary events, arising for the first time in the evolution of the genes under study. It becomes clear in this chapter that it is the actual rather than the observed number of states that is important. Having a large state space allows for a low level of predicted homoplasy, leading to one of the links reported between parsimony and likelihood. A related central question considered is how many characters are needed to recover unambiguously a phylogenetic tree? This chapter considers this for random models of state transition, and in the deterministic setting. It also considers the question of when, on a fixed tree, can the most parsimonious reconstruction of a character be expected to correspond exactly with its actual evolution.

Keywords:   likelihood, Markov model, state space, gene order, homoplasy

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