FastME 2.0: a comprehensive, accurate and fast distance-based phylogeny inference program.

Lefort V., Desper R., Gascuel O.

FastME provides distance algorithms to infer phylogenies. FastME is based on balanced minimum evolution, which is the very principle of NJ. FastME improves over NJ by performing topological moves using fast, sophisticated algorithms. The first version of FastME only included Nearest Neighbor Interchange (NNI). The new 2.0 version also includes Subtree Pruning and Regrafting (SPR), while remaining as fast as NJ and providing a number of facilities: distance estimation for DNA and proteins with various models and options, bootstrapping, and parallel computations.

FastME is now available on GitLab.

Running FastME

FastME is a software whose main task is to estimate phylogenies using distance methods from nucleotide or amino acid multiple sequences alignments (MSA). It provides a wide range of options that were designed to ease standard phylogenetic analyses. The main strengths of FastME lies the availability of several distance algorithms and optimization principles (OLS and Balanced Minimum Evolution, iterative taxon addition, NJ, UNJ, BioNJ) for tree estimation coupled with various options to search the space of phylogenetic tree topologies (NNIs, SPRs). It also provides a parallelized implementation of the non-parametric bootstrap method to evaluate branch supports.

You can use FastME with PHYLIP-like interface or with the command line.

More explanations are given in the FastME manual.

PHYLIP-like interface options

The interface always suggests the more relevant parameters.

Command line options

For example, assuming that the matrix datatest file (downloaded from this web page, see above) is within /home/ directory, the command line :
fastme –i /home/datatest.txt –d 3
will construct three trees and write them (Newick format) into the outputtree file '/home/dataset.txt_fastme_tree.nwk'. A second file '/home/dataset.txt_fastme_stat.txt' is created, containing options selected by the user and some statistics (estimated tree length and number of NNIs performed).