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Bioinformatics Advance Access originally published online on November 16, 2006
Bioinformatics 2007 23(2):169-176; doi:10.1093/bioinformatics/btl577
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© 2006 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Tree and rate estimation by local evaluation of heterochronous nucleotide data

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

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 Department of Mathematics, University of California Los Angeles, Los Angeles, CA 90095, USA

*To whom correspondence should be addressed.


  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

Contact: jdobrien{at}ucla.edu

{dagger}The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.

Associate Editor: Joaquin Dopazo

Received on April 1, 2006; revised on November 8, 2006; accepted on November 10, 2006

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