FastME 2.0: A Comprehensive, Accurate, and Fast Distance-Based Phylogeny Inference Program

By Vincent Lefort, Richard Desper, Olivier Gascuel. Molecular biology and evolution, 2015

1,649 citations recorded by the source corpus.

FastME provides distance algorithms to infer phylogenies. FastME is based on balanced minimum evolution, which is the very principle of Neighbor Joining (NJ). FastME improves over NJ by performing topological moves using fast, sophisticated algorithms. The first version of FastME only included Nearest Neighbor Interchange. The new 2.0 version also includes Subtree Pruning and Regrafting, 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 available using several interfaces: Command-line (to be integrated in pipelines), PHYLIP-like, and a Web server (http://www.atgc-montpellier.fr/fastme/).

Subfields: Genetics, Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/c3be104fa2907b78a2f1b58d037eee5798a2d7ca

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Citations in the corpus

NGPhylogeny.fr: new generation phylogenetic services for non-specialists (2019, methodology): “The four ‘ One click ’ workflows differ only at the tree inference step, which can be performed by FastTree (22), FastME (4), PhyML (3) or PhyML+SMS (24).”
GrapeTree: visualization of core genomic relationships among 100,000 bacterial pathogens (2017, positive): “NJ trees were calculated with FastMEV2 (Lefort et al. 2015) and RapidNJ (Simonsen et al. 2011).”
VICTOR: genome-based phylogeny and classification of prokaryotic viruses (2017, methodology): “4 (Lefort et al. 2015) and SPR branch swapping (Farris 1972) and rooted using the midpoint method (Hess and De Moraes Russo 2007).”
Fast Dating Using Least-Squares Criteria and Algorithms (2015, positive): “…combine them with fast tree-building methods, for example distance-based methods (e.g., NJ, Saitou and Nei 1987, or FastME, Desper and Gascuel 2002, Lefort et al. 2015), but more accurate results are expected from trees obtained using maximum-likelihood (ML) methods (e.g., PhyML, Guindon and…”