Skip Navigation



Bioinformatics Advance Access published online on November 16, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl577
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrowOA All Versions of this Article:
23/2/169    most recent
btl577v1
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
Google Scholar
Right arrow Articles by Yang, Z.
Right arrow Articles by She, Z.-S.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Yang, Z.
Right arrow Articles by She, Z.-S.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 2006 The Author(s)
Received April 1, 2006
Revised November 8, 2006
Accepted November 10, 2006

Article

Tree and rate estimation by local evaluation of heterochronous nucleotide data

Zhu Yang 1 *, John D. O'Brien 2 *, Xiaobin Zheng 1, Huai-Qiu Zhu 1, and Zhen-Su She 3 *

1 State Key Lab for Turbulence and Complex Systems and Center for Theoretical Biology, Peking University, Beijing 100871, China
2 Department of Biomathematics, University of California, Los Angeles, Los Angeles, CA 90095, USA
3 State Key Lab for Turbulence and Complex Systems and Center for Theoretical Biology, Peking University, Beijing 100871, China; Department of Mathematics, University of California, Los Angeles, Los Angeles, CA 90095, USA

* To whom correspondence should be addressed.
Zhen-Su She, E-mail: she{at}math.ucla.edu


  Abstract

Motivation: Heterochronous gene sequence data is important for characterizing the evolutionary processes of fast-evolving organisms such as RNA viruses. A limited set of algorithms exists for estimating the rate of nucleotide substitution and inferring phylogenetic trees from such data. The authors here present a new method, Tree and Rate Estimation by Local Evaluation (TREBLE), that robustly calculates the rate of nucleotide substitution and phylogeny with several orders of magnitude improvement in computational time.

Methods: For the basis of its rate estimation TREBLE novelly utilizes a geometric interpretation of the molecular clock assumption to deduce a local estimate of the rate of nucleotide substitution for triplets of dated sequences. Averaging the triplet estimates via a variance weighting yields a global estimate of the rate. From this value, an iterative refinement procedure relying on statistical properties of the triplets then generates a final estimate of the global rate of nucleotide substitution. The estimated global rate is then utilized to find the tree from the pairwise distance matrix via an UPGMA-like algorithm.

Results: Simulation studies show that TREBLE estimates the rate of nucleotide substitution with point estimates comparable with the best of available methods. Confidence intervals are comparable with that of BEAST. TREBLE's phylogenetic reconstruction is significantly improved over the other distance matrix method but not as accurate as the Bayesian algorithm. Compared with three other algorithms, TREBLE reduces computational time by a minimum factor of 3000. Relative to the algorithm with the most accurate estimates for the rate of nucleotide substitution (i.e. BEAST), TREBLE is over 10,000 times more computationally efficient.

Availability: jdobrien.bol.ucla.edu/TREBLE.html.

Associate Editor: Joaquin Dopazo

*These authors contributed equally to this work.


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
V. N. Minin, E. W. Bloomquist, and M. A. Suchard
Smooth Skyride through a Rough Skyline: Bayesian Coalescent-Based Inference of Population Dynamics
Mol. Biol. Evol., July 1, 2008; 25(7): 1459 - 1471.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
P. Buendia and G. Narasimhan
Sliding MinPD: building evolutionary networks of serial samples via an automated recombination detection approach
Bioinformatics, November 15, 2007; 23(22): 2993 - 3000.
[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.