Bioinformatics Advance Access published online on April 1, 2004
Bioinformatics, doi:10.1093/bioinformatics/bth211
Bioinformatics © Oxford University Press 2004; all rights reserved
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1 Département d'Informatique, Université du Québec à Montréal, C.P. 8888, Succ. Centre-Ville, Montréal (Québec), Canada, H3C 3P8; Institute of Control Sciences, 65 Profsoyuznaya, Moscow 117806, Russia
* To whom correspondence should be addressed. E-mail: makarenkov.vladimir{at}uqam.ca.
Motivation: The problem of phylogenetic inference from data sets including incomplete or uncertain entries is among the most relevant issues in systematic biology. In this paper, we propose a new method for reconstructing phylogenetic trees from partial distance matrices. The new method combines the usage of the four-point condition and the ultrametric inequality with a weighted least-squares approximation to solve the problem of missing entries. It can be applied to infer phylogenies from evolutionary data including some missing or uncertain information, for instance, when observed nucleotide or protein sequences contain gaps or missing entries. Results: In a number of simulations involving incomplete data sets, the proposed method outperformed the well-known Ultrametric and Additive procedures. Generally, the new method also outperformed all the other competing approaches including Triangle and Fitch which is the most popular least-squares method for reconstructing phylogenies. We illustrate the usefulness of the introduced method by analyzing two well-known phylogenies derived from complete mammalian mtDNA sequences (see Cao et al., 1998, Reyes et al., 2000, and Li et al., 2001). Some interesting theoretical results concerning the NP-hardness of the ordinary and weighted least-squares fitting of a phylogenetic tree to a partial distance matrix are also established. Availability: The T-Rex package (Makarenkov, 2001a) including this method is freely available for download at: http://www.fas.umontreal.ca/biol/casgrain/en/labo/t-rex.
Revised February 20, 2004
Accepted February 20, 2004
Article
A weighted least-squares approach for inferring phylogenies from incomplete distance matrices
2 Département de Sciences Biologiques, Université de Montréal, C.P. 6128, succ. Centre-ville, Montréal, Québec H3C 3J7, Canada
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