Partitioned likelihood support and the evaluation of data set conflict

Lee, M. S. Y. and Hugall, A. F. (2003) Partitioned likelihood support and the evaluation of data set conflict. Systematic Biology, 52 1: 15-22. doi:10.1080/10635150390132650

Author Lee, M. S. Y.
Hugall, A. F.
Title Partitioned likelihood support and the evaluation of data set conflict
Journal name Systematic Biology   Check publisher's open access policy
ISSN 1063-5157
Publication date 2003-01-01
Sub-type Article (original research)
DOI 10.1080/10635150390132650
Volume 52
Issue 1
Start page 15
End page 22
Total pages 8
Place of publication Philadelphia, USA
Publisher Taylor & Francis Inc
Language eng
Subject C1
270402 Plant Physiology
620302 Softwood plantations
Abstract In simultaneous analyses of multiple data partitions, the trees relevant when measuring support for a clade are the optimal tree, and the best tree lacking the clade (i.e., the most reasonable alternative). The parsimony-based method of partitioned branch support (PBS) forces each data set to arbitrate between the two relevant trees. This value is the amount each data set contributes to clade support in the combined analysis, and can be very different to support apparent in separate analyses. The approach used in PBS can also be employed in likelihood: a simultaneous analysis of all data retrieves the maximum likelihood tree, and the best tree without the clade of interest is also found. Each data set is fitted to the two trees and the log-likelihood difference calculated, giving partitioned likelihood support (PLS) for each data set. These calculations can be performed regardless of the complexity of the ML model adopted. The significance of PLS can be evaluated using a variety of resampling methods, such as the Kishino-Hasegawa test, the Shimodiara-Hasegawa test, or likelihood weights, although the appropriateness and assumptions of these tests remains debated.
Keyword Evolutionary Biology
Kishino-hasegawa Test
Partitioned Branch Support
Partitioned Likelihood Support
Shimodaira-hasegawa Test
Templeton Test
Mitochondrial-dna Sequences
Statistical Tests
Extant Taxa
Q-Index Code C1

Document type: Journal Article
Sub-type: Article (original research)
Collections: 2004 Higher Education Research Data Collection
School of Agriculture and Food Sciences
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 47 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 53 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Wed, 15 Aug 2007, 12:23:58 EST