SMS: smart model selection in PhyML
V Lefort, JE Longueville… - Molecular biology and …, 2017 - academic.oup.com
V Lefort, JE Longueville, O Gascuel
Molecular biology and evolution, 2017•academic.oup.comAbstract Model selection using likelihood-based criteria (eg, 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 …
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 …
Abstract
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