MetaPIGA, a versatile and easy-to-use software developped by the laboratory of Prof. Milinkovitch, has just reached version 3.1.
The program implements robust stochastic heuristics (including the Metapopulation Genetic Algorithm, metaGA) for large phylogeny inference under Maximum Likelihood.
It allows analyses of binary (for example morphological) and molecular (nucleotides, amino-acids, and codons) data sets under multiple substitution models, Gamma rate heterogeneity, and data partitioning.
The software is for all types of users as it can be run through an extensive and ergonomic graphical interface, or by using batch ﬁles and console interface on your local machine or on distant servers.
MetaPIGA is platform independent, runs on 32- and 64-bits systems, and easily takes advantage of multiprocessor and/or multicore computers.
Version 3.1 of MetaPIGA includes new functionalities such as ancestral-state reconstruction (using empirical Bayesian inference) and Likelihood computation on CUDA-compatible Nvidia graphic cards (reducing run time by a factor of 10 to 20 for Protein/Codon data).