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SMS: Smart Model Selection in PhyML
Model selection using likelihood-based criteria (e.g., AIC) is one of the first steps in phylogenetic analysis. One must select both a substitution matrix and a model for rates across sites. A simple method is to test all combinations and select the best one. We describe heuristics to avoid these ex...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5850602/ https://www.ncbi.nlm.nih.gov/pubmed/28472384 http://dx.doi.org/10.1093/molbev/msx149 |
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author | Lefort, Vincent Longueville, Jean-Emmanuel Gascuel, Olivier |
author_facet | Lefort, Vincent Longueville, Jean-Emmanuel Gascuel, Olivier |
author_sort | Lefort, Vincent |
collection | PubMed |
description | Model selection using likelihood-based criteria (e.g., AIC) is one of the first steps in phylogenetic analysis. One must select both a substitution matrix and a model for rates across sites. A simple method is to test all combinations and select the best one. We describe heuristics to avoid these extensive calculations. Runtime is divided by ∼2 with results remaining nearly the same, and the method performs well compared with ProtTest and jModelTest2. Our software, “Smart Model Selection” (SMS), is implemented in the PhyML environment and available using two interfaces: command-line (to be integrated in pipelines) and a web server (http://www.atgc-montpellier.fr/phyml-sms/). |
format | Online Article Text |
id | pubmed-5850602 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-58506022018-03-23 SMS: Smart Model Selection in PhyML Lefort, Vincent Longueville, Jean-Emmanuel Gascuel, Olivier Mol Biol Evol Resources Model selection using likelihood-based criteria (e.g., AIC) is one of the first steps in phylogenetic analysis. One must select both a substitution matrix and a model for rates across sites. A simple method is to test all combinations and select the best one. We describe heuristics to avoid these extensive calculations. Runtime is divided by ∼2 with results remaining nearly the same, and the method performs well compared with ProtTest and jModelTest2. Our software, “Smart Model Selection” (SMS), is implemented in the PhyML environment and available using two interfaces: command-line (to be integrated in pipelines) and a web server (http://www.atgc-montpellier.fr/phyml-sms/). Oxford University Press 2017-09 2017-05-11 /pmc/articles/PMC5850602/ /pubmed/28472384 http://dx.doi.org/10.1093/molbev/msx149 Text en © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Resources Lefort, Vincent Longueville, Jean-Emmanuel Gascuel, Olivier SMS: Smart Model Selection in PhyML |
title | SMS: Smart Model Selection in PhyML |
title_full | SMS: Smart Model Selection in PhyML |
title_fullStr | SMS: Smart Model Selection in PhyML |
title_full_unstemmed | SMS: Smart Model Selection in PhyML |
title_short | SMS: Smart Model Selection in PhyML |
title_sort | sms: smart model selection in phyml |
topic | Resources |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5850602/ https://www.ncbi.nlm.nih.gov/pubmed/28472384 http://dx.doi.org/10.1093/molbev/msx149 |
work_keys_str_mv | AT lefortvincent smssmartmodelselectioninphyml AT longuevillejeanemmanuel smssmartmodelselectioninphyml AT gascuelolivier smssmartmodelselectioninphyml |