HPC selection of models of nucleotide substitution
jModelTest is a tool to carry out statistical selection of best-fit
models of nucleotide substitution. It implements five different model
selection strategies: hierarchical and dynamical likelihood ratio tests
(hLRT and dLRT), Akaike and Bayesian information criteria (AIC and BIC),
and a decision theory method (DT). It also provides estimates of model
selection uncertainty, parameter importances and model-averaged
parameter estimates, including model-averaged tree topologies.
jModelTest 2 includes High Performance Computing (HPC) capabilities and
additional features like new strategies for tree optimization, model-
averaged phylogenetic trees (both topology and branch length), heuristic
filtering and automatic logging of user activity.
