Skip Navigation



MBE Advance Access published online on April 25, 2003
Molecular Biology and Evolution, doi:10.1093/molbev/msg093
Molecular Biology and Evolution © Society for Molecular Biology and Evolution 2003; all rights reserved
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrow All Versions of this Article:
20/6/862    most recent
msg093v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Susko, E.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Susko, E.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Accepted January 21, 2003
© 2003 Society for Molecular Biology and Evolution

Original Articles

Confidence Regions and Hypothesis Tests for Topologies Using Generalized Least Squares

Edward Susko 1*

1 Department of Mathematics and Statistics, Dalhousie University

* To whom correspondence should be addressed. E-mail: susko{at}mathstat.dal.ca.


  Abstract

A confidence region for topologies is a data-dependent set of topologies that, with high probability, can be expected to contain the true topology. Because of the connection between confidence regions and hypothesis tests, implicitly or explicitly, the construction of confidence regions for topologies is a component of many phylogenetic studies. Existing methods for constructing confidence regions, however, often give conflicting results. The SH test seems too conservative, including too many topologies, while the other commonly used method, the SOWH test tends to give confidence regions with too few topologies. Confidence regions are constructed here based upon a generalized least squares test statistic. The methodology described is computationally inexpensive and broadly applicable to maximum likelihood distances. Assuming the model used to construct the distances is correct, the coverage probabilities are correct with large numbers of sites.

Key Words: generalized least squares, phylogeny, statistical tests


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Mol Biol EvolHome page
X. Shi, H. Gu, and C. Field
Test a Clade in Phylogenetic Trees
Mol. Biol. Evol., October 1, 2006; 23(10): 1976 - 1983.
[Abstract] [Full Text] [PDF]

Home page
 Mol Biol EvolHome page
X. Shi, H. Gu, E. Susko, and C. Field
The Comparison of the Confidence Regions in Phylogeny
Mol. Biol. Evol., November 1, 2005; 22(11): 2285 - 2296.
[Abstract] [Full Text] [PDF]

Home page
 Syst BiolHome page
R. Sanjuan and B. Wrobel
Weighted Least-Squares Likelihood Ratio Test for Branch Testing in Phylogenies Reconstructed from Distance Measures
Syst Biol, April 1, 2005; 54(2): 218 - 229.
[Abstract] [Full Text] [PDF]

Home page
 Mol Biol EvolHome page
R. Desper and O. Gascuel
Theoretical Foundation of the Balanced Minimum Evolution Method of Phylogenetic Inference and Its Relationship to Weighted Least-Squares Tree Fitting
Mol. Biol. Evol., March 1, 2004; 21(3): 587 - 598.
[Abstract] [Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.