期刊
MOLECULAR BIOLOGY AND EVOLUTION
卷 30, 期 6, 页码 1270-1280出版社
OXFORD UNIV PRESS
DOI: 10.1093/molbev/mst034
关键词
maximum likelihood; phylogeny inference; codon model; evolution; selection
资金
- Swiss Federal Commission [2006.0091]
- Swiss National Science Foundation (SNF) [31003A_127325/1, PBEZP2_140129, CR12I1_125298]
- Swiss National Science Foundation (SNF) [CR12I1_125298, PBEZP2_140129] Funding Source: Swiss National Science Foundation (SNF)
Markov models of codon substitution naturally incorporate the structure of the genetic code and the selection intensity at the protein level, providing a more realistic representation of protein-coding sequences compared with nucleotide or amino acid models. Thus, for protein-coding genes, phylogenetic inference is expected to be more accurate under codon models. So far, phylogeny reconstruction under codon models has been elusive due to computational difficulties of dealing with high dimension matrices. Here, we present a fast maximum likelihood (ML) package for phylogenetic inference, CodonPhyML offering hundreds of different codon models, the largest variety to date, for phylogeny inference by ML. CodonPhyML is tested on simulated and real data and is shown to offer excellent speed and convergence properties. In addition, CodonPhyML includes most recent fast methods for estimating phylogenetic branch supports and provides an integral framework for models selection, including amino acid and DNA models.
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