Parsimony and the problem of inapplicables in sequence data

© Oxford University Press 2005. All rights reserved. Problems can arise in parsimony analyses when data sets contain characters that are not applicable across all terminals. Examples of such characters are tail colour when some terminals lack tails, or positions in DNA sequences in which gaps are present. Focusing on regular single-column characters as classically used in phylogenetic analysis, Farris characterized parsimony as a method that maximizes explanatory power in the sense that most-parsimonious trees are best able to explain observed similarities among organisms by inheritance and common ancestry. This led De Laet to formulate parsimony analysis as two-item analysis, whereby parsimony maximizes the number of observed pairwise similarities that can be explained as identical by virtue of common descent, subject to two methodological constraints: the same evidence should not be taken into account multiple times, and the overall explanation must be free of internal contradictions. In this chapter, the way this formulation can be used to deal with the problem of inapplicables is discussed vis-à-vis the optimization of entire nucleotide sequences as complex characters in a tree alignment.status: publishe