The limits of conventional cladistic analysis

Jerrold I. Davis, Kevin C. Nixon and Damon P. Little

in Parsimony, Phylogeny, and Genomics

Published in print March 2006 | ISBN: 9780199297306
Published online September 2007 | e-ISBN: 9780191713729 | DOI:
 The limits of conventional cladistic analysis

Show Summary Details


Software for cladistic analysis has been widely available for more than twenty years, and a series of advances made during this time have facilitated the analysis of matrices of ever-increasing size. This chapter provides an overview of the development of parsimony methods for cladistic analysis, describes strategies that have allowed large data matrices to be analysed by conventional methods, and in doing so, demonstrates that data sets historically considered intracable could in fact have been readily approached using then-available hardware and software. Preliminary analyses, even when unsuccessful at discovering most-parsimonious trees, can be used to identify appropriate software settings for use during thorough analyses. A useful indicator of the settings that yield the most efficient searches is the excess branch swapping ratio, which is the ratio between the number of tree rearrangements conducted during a particular phase of branch swapping in which shorter trees are being discovered, and the minimum possible number of rearrangements during this phase. It is concluded that two-stage search strategies, with intensive branch swapping conducted on a small percentage of the most optimal sets of trees obtained by a large number of relatively short searches, are more efficient than one-stage searches.

Keywords: parsimony methods; large data sets; excess branch swapping ration; rearrangements; two-stage searches; one-stage searches

Chapter.  18851 words.  Illustrated.

Subjects: Evolutionary Biology

Full text: subscription required

How to subscribe Recommend to my Librarian

Buy this work at Oxford University Press »

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content. subscribe or login to access all content.