Phylogenetic Likelihood Library

libPLL: The Phylogenetic Likelihood Library is a highly optimized and parallelized library for rapid prototyping and development of likelihood based phylogenetic inference codes. libPLL is the core of RAxML-NG, ModelTest-NG and EPA-NG, among others.

Flouri T, Izquierdo-Carrasco F, Darriba D, Aberer AJ, Nguyen LT, Minh BQ, Von Haeseler A. Stamatakis A. The phylogenetic likelihood library. Systematic biology, 64(2):356-362, 2014

jModelTest 2

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 lenght), heuristic filtering and automatic logging of user activity.

Darriba D, Taboada GL, Doallo R, Posada D. jModelTest 2: more models, new heuristics and parallel computing. Nature Methods 9:772, 2012

ProtTest 3

ProtTest is a bioinformatic tool for the selection of best-fit models of aminoacid replacement for the data at hand. ProtTest makes this selection by finding the model in the candidate list with the smallest Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) score or Decision Theory Criterion (DT). At the same time, ProtTest obtains model-averaged estimates of different parameters (including a model-averaged phylogenetic tree) and calculates their importance (Posada and Buckley 2004). ProtTest differs from its nucleotide analog jModeltest (Posada 2008) in that it does not include likelihood ratio tests, as not all models included in ProtTest are nested.

Darriba D, Taboada GL, Doallo R, Posada D. ProtTest 3: fast selection of best-fit models of protein evolution. Bioinformatics, 27:1164-1165, 2011

ForeSeqs

ForeSeqs is a tool for predicting sequences in data sets with whole missing partitions. Missing data usually lead to wrong phylogenetic inferences, since branches leading to unexistent taxa can have arbitrary lengths. Terraces in the phylogenetic tree space is another problem derived from missing taxa. Even though this problem can be avoided by linking branch lengths across partitions, the missing data can affect the inferences.

Darriba D, Weiss M, Stamatakis A: Prediction of missing sequences and branch lengths in phylogenomic data. Bioinformatics 32(9):1331-1337, 2016

TreeChar

TreeChar is a tool for characterizing the phylogenetic tree space. Maximum-Likelihood heuristic makes assumptions on the phylogenetic tree space. However, little is known about the effect of the data characteristics on the likelihood surface, as long as it is usually not feasible to evaluate the whole tree space, which grows exponentially with the number of taxa.