Current practices for model selection (e.g., AIC, BIC) are aimed at finding the underlying model, but don't always produce the most accurate phylogeny.
ModelTeller is a machine-learning based application that predicts the best substitution model for phylogenetic reconstruction,
with an emphasis on branch-lengths accuracy! Output:
1. The best predicted model and the ranking of alternative models, in case that you cannot use the best model in downstream analysis.
ModelTeller will return the best model, and the ranking of alternative models among the following 24 nucleotide substitution models:
Jukes and Cantor 1969 (JC)
Felsenstein 1981 (F81)
Kimura two parameters 1980 (K2P)
Hasegawa-Kishino-Yano 1985 (HKY)
The generalized symmetrical model, Zharkikh, 1994 (SYM)
General Time Reversible, Tavare 1986 (GTR)
combined with the proportion of invariable sites (+I), rate heterogeneity across sites (+G), or both (+I+G).
2. The maximum-likelihood tree, reconstructed using the best model.
3. The feature contribution analysis to learn the weight of every feature in the prediction.