Gtr model evolution
2009).ĭistances: During these minimum evolution steps, FastTree needs to estimate distances between sequences or profiles.Įstimates distances by using the BLOSUM45 amino acid similarity ( Desper & Gascuel 2004, Bordewich et al. NNI and SPR moves suffice to reach optimal trees In the minimum-evolution framework, if the distances are not too noisy, The best choice in the chain for chains of length two or greater. Treats SPR moves as chains of NNIs and only extends In each round, it considers every possible NNI in the tree.īecause there are too many (O(N 2)) possible SPR moves, FastTree These "balanced minimum-evolution" rearrangements are roughly the same as whatįastME does, but because FastTree uses profiles instead of distances,īy default, FastTree uses 4*log 2(N) rounds of nearest-neighbor interchanges and 2 rounds of subtree-prune-regraft Minimum EvolutionįastTree then tries to reduce the length of the tree, However, this will be corrected in the next stage. It also updates the best join for a node as it comes across them, which reducesĪnother limitation of FastTree's neighbor-joining phase is that it does not correct the distancesįor multiple substitutions, which exacerbates long-branch attraction. It does a hill-climbing search for better joins from a candidate join, as inĪnd it uses the "top hits" heuristic to avoid computing all pairwise distancesĪnd to avoid considering all possible joins at every step. It remembers the best join for each node, as in Maximizing the tree's likelihood with NNIsįirst, FastTree uses a heuristic variant ofĭuring neighbor joining, FastTree stores profiles of internal nodes instead of a distance matrix,įastTree uses a combination of three heuristics to speed up this phase:.(2010) FastTree 2 - Approximately Maximum-Likelihood Trees for Large Alignments. Price, M.N., Dehal, P.S., and Arkin, A.P.
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(2009) FastTree: Computing Large Minimum-Evolution Trees with Profiles instead of a Distance Matrix. We have also eliminated the O(N 2) steps in the neighbor-joining phase,Īnd implemented maximum-likelihood NNI moves and SH-like supports (see the ChangeLog). These papers describe FastTree: the first paper describes FastTree 1.0, and the second paper describes heuristic minimum-evolution SPR moves, maximum-likelihood NNIs, and SH-like local supports. CAT/Gamma20 branch lengths and likelihoods.Pseudocounts for highly fragmentary sequences.Shimodaira-Hasegawa test (these are the same as PhyML 3's "SH-like local supports"). To quickly estimate the reliability of each split in the tree, FastTree computes To account for the varying rates of evolution across sites,įastTree uses a single rate for each site (the "CAT" approximation). FastTree 2.1: Approximately-Maximum-Likelihood Trees for Large Alignments FastTreeįastTree infers approximately-maximum-likelihood phylogenetic trees from alignments of nucleotide or protein sequences.įastTree can handle alignments with up to a million of sequences in a reasonable amount of time and memory.įor large alignments, FastTree is 100-1,000 times faster thanįastTree is open-source software - you can download the code below.įastTree is more accurate than PhyML 3 with default settings,Īnd much more accurate than the distance-matrix methods that are traditionally usedįastTree uses the Jukes-Cantor or generalized time-reversible (GTR) models of nucleotide evolution and the JTT ( Jones-Taylor-Thornton 1992), WAG ( Whelan & Goldman 2001), or LG ( Le and Gascuel 2008) models of amino acid evolution.