A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood

The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on the maximum-likelihood principle, which clearly satisfies these requirements. The...

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Veröffentlicht in:Systematic biology Jg. 52; H. 5; S. 696 - 704
Hauptverfasser: Guindon, Stéphane, Gascuel, Olivier, Rannala, Bruce
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England Society of Systematic Zoology 01.10.2003
Taylor and Francis
Oxford University Press
Schlagworte:
Algorithm
Algorithms
Computer Simulation
computer simulations
Datasets
Evolution
Evolution, Molecular
Inference
Likelihood Functions
maximum likelihood
Maximum likelihood estimation
Models, Genetic
Parsimony
Phylogenetics
Phylogeny
PHYML program
Probability
rbcL
RDPII project
Taxa
Topology
phylogeny
computer simulations
L
Algorithm
RDPII project
maximum likelihood
ISSN:1063-5157, 1076-836X
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Zusammenfassung:The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on the maximum-likelihood principle, which clearly satisfies these requirements. The core of this method is a simple hill-climbing algorithm that adjusts tree topology and branch lengths simultaneously. This algorithm starts from an initial tree built by a fast distance-based method and modifies this tree to improve its likelihood at each iteration. Due to this simultaneous adjustment of the topology and branch lengths, only a few iterations are sufficient to reach an optimum. We used extensive and realistic computer simulations to show that the topological accuracy of this new method is at least as high as that of the existing maximum-likelihood programs and much higher than the performance of distance-based and parsimony approaches. The reduction of computing time is dramatic in comparison with other maximum-likelihood packages, while the likelihood maximization ability tends to be higher. For example, only 12 min were required on a standard personal computer to analyze a data set consisting of 500 rbc L sequences with 1,428 base pairs from plant plastids, thus reaching a speed of the same order as some popular distance-based and parsimony algorithms. This new method is implemented in the PHYML program, which is freely available on our web page: http://www.lirmm.fr/w3ifa/MAAS/.
Bibliographie:istex:10D069593FA116F90817B5F2773320087F8156B0
ark:/67375/HXZ-32P26Z5L-9
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ISSN:1063-5157
1076-836X
DOI:10.1080/10635150390235520