FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments
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{"title"=>"FastTree 2 - Approximately maximum-likelihood trees for large alignments", "type"=>"journal", "authors"=>[{"first_name"=>"Morgan N.", "last_name"=>"Price", "scopus_author_id"=>"8849984000"}, {"first_name"=>"Paramvir S.", "last_name"=>"Dehal", "scopus_author_id"=>"6602411350"}, {"first_name"=>"Adam P.", "last_name"=>"Arkin", "scopus_author_id"=>"7006902792"}], "year"=>2010, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"358498937", "sgr"=>"77949718257", "issn"=>"19326203", "arxiv"=>"Price, Morgan N., 2010, FastTree 2", "pmid"=>"20224823", "scopus"=>"2-s2.0-77949718257", "doi"=>"10.1371/journal.pone.0009490", "isbn"=>"1932-6203"}, "id"=>"06e20bd9-e6e5-3810-bcb8-792ee2f520d4", "abstract"=>"We recently described FastTree, a tool for inferring phylogenies for alignments with up to hundreds of thousands of sequences. Here, we describe improvements to FastTree that improve its accuracy without sacrificing scalability.", "link"=>"http://www.mendeley.com/research/fasttree-2-approximately-maximumlikelihood-trees-large-alignments", "reader_count"=>1501, "reader_count_by_academic_status"=>{"Unspecified"=>40, "Professor > Associate Professor"=>61, "Researcher"=>372, "Student > Doctoral Student"=>72, "Student > Ph. D. Student"=>491, "Student > Postgraduate"=>55, "Student > Master"=>198, "Other"=>46, "Student > Bachelor"=>113, "Lecturer"=>15, "Lecturer > Senior Lecturer"=>4, "Professor"=>33}, "reader_count_by_user_role"=>{"Unspecified"=>40, "Professor > Associate Professor"=>61, "Researcher"=>372, "Student > Doctoral Student"=>72, "Student > Ph. D. Student"=>491, "Student > Postgraduate"=>55, "Student > Master"=>198, "Other"=>46, "Student > Bachelor"=>113, "Lecturer"=>15, "Lecturer > Senior Lecturer"=>4, "Professor"=>33}, "reader_count_by_subject_area"=>{"Unspecified"=>86, "Agricultural and Biological Sciences"=>915, "Arts and Humanities"=>4, "Veterinary Science and Veterinary Medicine"=>9, "Chemical Engineering"=>1, "Chemistry"=>8, "Computer Science"=>52, "Earth and Planetary Sciences"=>21, "Engineering"=>17, "Environmental Science"=>82, "Biochemistry, Genetics and Molecular Biology"=>188, "Materials Science"=>1, "Mathematics"=>13, "Medicine and Dentistry"=>49, "Neuroscience"=>1, "Design"=>1, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Physics and Astronomy"=>1, "Psychology"=>2, "Social Sciences"=>2, "Immunology and Microbiology"=>46}, "reader_count_by_subdiscipline"=>{"Materials Science"=>{"Materials Science"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>49}, "Social Sciences"=>{"Social Sciences"=>2}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Psychology"=>{"Psychology"=>2}, "Mathematics"=>{"Mathematics"=>13}, "Unspecified"=>{"Unspecified"=>86}, "Environmental Science"=>{"Environmental Science"=>82}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}, "Chemical Engineering"=>{"Chemical Engineering"=>1}, "Arts and Humanities"=>{"Arts and Humanities"=>4}, "Design"=>{"Design"=>1}, "Engineering"=>{"Engineering"=>17}, "Chemistry"=>{"Chemistry"=>8}, "Neuroscience"=>{"Neuroscience"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>21}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>46}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>915}, "Computer Science"=>{"Computer Science"=>52}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>188}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>9}}, "reader_count_by_country"=>{"United States"=>62, "Thailand"=>1, "Greece"=>1, "Sweden"=>8, "Netherlands"=>8, "Korea (South)"=>1, "China"=>1, "Brazil"=>17, "Poland"=>1, "France"=>9, "Chile"=>4, "Colombia"=>1, "Argentina"=>1, "Japan"=>1, "United Kingdom"=>16, "Zambia"=>1, "Switzerland"=>2, "Spain"=>7, "India"=>3, "Palestine"=>1, "New Zealand"=>2, "Canada"=>13, "Czech Republic"=>7, "Burkina Faso"=>1, "Belgium"=>7, "Norway"=>4, "Finland"=>1, "Denmark"=>7, "Mexico"=>4, "South Africa"=>2, "Italy"=>1, "Israel"=>1, "Australia"=>4, "Germany"=>16, "Estonia"=>1}, "group_count"=>59}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/859331"], "description"=>"<p>FastTree optimizes the tree near node N by analyzing the posterior distributions for subtrees A, B, and C, as well as the “up-posterior” D.</p>", "links"=>[], "tags"=>["computational biology/macromolecular sequence analysis", "evolutionary biology/bioinformatics", "molecular biology/molecular evolution"], "article_id"=>529792, "categories"=>["Evolutionary Biology", "Medicine", "Molecular Biology"], "users"=>["Morgan N. Price", "Paramvir S. Dehal", "Adam P. Arkin"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0009490.g003", "stats"=>{"downloads"=>2, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Traversing_a_tree_with_up_posteriors_/529792", "title"=>"Traversing a tree with up-posteriors.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-03-10 02:43:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/859248"], "description"=>"<p>Each line shows the time it takes a different tool to reach a given likelihood. For the COG alignments, all times and likelihoods are averages over the seven alignments. For FastTree, we show the time and the improvement in likelihood for the minimum-evolution topology and the final (approximately-ML) topology. For RAxML, we show the maximum parsimony starting topology, the first two rounds of SPR moves, and the final topology (note the interrupted axis). For RAxML with FastTree's (minimum-evolution) starting tree, we show the starting topology and RAxML's first two rounds of SPR moves.</p>", "links"=>[], "tags"=>["computational biology/macromolecular sequence analysis", "evolutionary biology/bioinformatics", "molecular biology/molecular evolution"], "article_id"=>529709, "categories"=>["Evolutionary Biology", "Medicine", "Molecular Biology"], "users"=>["Morgan N. Price", "Paramvir S. Dehal", "Adam P. Arkin"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0009490.g002", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Likelihoods_over_time_for_genuine_alignments_/529709", "title"=>"Likelihoods over time for genuine alignments.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-03-10 02:41:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/859375"], "description"=>"<p>All runs used a single thread of execution. All runs accounted for variable rates across sites, using CAT for RAxML 7 and FastTree 2 or for PhyML 3. All FastTree runs include local SH-like supports and all RAxML runs include branch lengths under . RAxML and PhyML were run without support values (no bootstrap). For random subsets of 500 16S rRNAs or for COGs, we show average running times. For alignments with over 1,000 sequences, we used RAxML 7.2.1's fast convergence option.</p>", "links"=>[], "tags"=>["usage"], "article_id"=>529837, "categories"=>["Evolutionary Biology", "Medicine", "Molecular Biology"], "users"=>["Morgan N. Price", "Paramvir S. Dehal", "Adam P. Arkin"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0009490.t004", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Running_time_and_memory_usage_on_genuine_alignments_/529837", "title"=>"Running time and memory usage on genuine alignments.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-03-10 02:43:57"}
  • {"files"=>["https://ndownloader.figshare.com/files/859407"], "description"=>"<p>For alignments with 5,000 sequences, we used RAxML 7.2.1 with fast convergence; for smaller alignments we used RAxML 7.0.4. An earlier version of PhyML 3 took up to 4 days for individual simulations with 1,250 sequences, even without , so we did not try to run PhyML 3 with on the larger simulations.</p>", "links"=>[], "tags"=>["trees", "inferred", "simulated"], "article_id"=>529862, "categories"=>["Evolutionary Biology", "Medicine", "Molecular Biology"], "users"=>["Morgan N. Price", "Paramvir S. Dehal", "Adam P. Arkin"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0009490.t001", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Topological_accuracy_of_trees_inferred_from_simulated_alignments_/529862", "title"=>"Topological accuracy of trees inferred from simulated alignments.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-03-10 02:44:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/426962", "https://ndownloader.figshare.com/files/427072", "https://ndownloader.figshare.com/files/427145"], "description"=>"<div><h3>Background</h3><p>We recently described FastTree, a tool for inferring phylogenies for alignments with up to hundreds of thousands of sequences. Here, we describe improvements to FastTree that improve its accuracy without sacrificing scalability.</p><h3>Methodology/Principal Findings</h3><p>Where FastTree 1 used nearest-neighbor interchanges (NNIs) and the minimum-evolution criterion to improve the tree, FastTree 2 adds minimum-evolution subtree-pruning-regrafting (SPRs) and maximum-likelihood NNIs. FastTree 2 uses heuristics to restrict the search for better trees and estimates a rate of evolution for each site (the “CAT” approximation). Nevertheless, for both simulated and genuine alignments, FastTree 2 is slightly more accurate than a standard implementation of maximum-likelihood NNIs (PhyML 3 with default settings). Although FastTree 2 is not quite as accurate as methods that use maximum-likelihood SPRs, most of the splits that disagree are poorly supported, and for large alignments, FastTree 2 is 100–1,000 times faster. FastTree 2 inferred a topology and likelihood-based local support values for 237,882 distinct 16S ribosomal RNAs on a desktop computer in 22 hours and 5.8 gigabytes of memory.</p><h3>Conclusions/Significance</h3><p>FastTree 2 allows the inference of maximum-likelihood phylogenies for huge alignments. FastTree 2 is freely available at <a href=\"http://www.microbesonline.org/fasttree\">http://www.microbesonline.org/fasttree</a>.</p></div>", "links"=>[], "tags"=>["fasttree", "maximum-likelihood", "trees", "alignments"], "article_id"=>144280, "categories"=>["Evolutionary Biology", "Medicine", "Molecular Biology"], "users"=>["Morgan N. Price", "Paramvir S. Dehal", "Adam P. Arkin"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0009490.s001", "https://dx.doi.org/10.1371/journal.pone.0009490.s002", "https://dx.doi.org/10.1371/journal.pone.0009490.s003"], "stats"=>{"downloads"=>7, "page_views"=>31, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/FastTree_2_Approximately_Maximum_Likelihood_Trees_for_Large_Alignments/144280", "title"=>"FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2010-03-10 01:11:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/859164"], "description"=>"<p>We examined local support values for the splits inferred by PhyML 3.0 with + SPRs on simulated alignments with 250 protein sequences. We classified PhyML's splits as correct and found by both PhyML and FastTree, correct but missed by FastTree, or incorrect. We show the distribution of support values for each class. The right-most bin includes the strongly supported splits (0.95 to 1.0), and the gray dashed line shows the uniform distribution. The support values are PhyML's minimum of the approximate likelihood ratio test <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0009490#pone.0009490-Anisimova1\" target=\"_blank\">[21]</a> and SH-like <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0009490#pone.0009490-Guindon2\" target=\"_blank\">[16]</a>, <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0009490#pone.0009490-Guindon3\" target=\"_blank\">[17]</a> local supports.</p>", "links"=>[], "tags"=>["splits", "phyml", "spr", "moves"], "article_id"=>529622, "categories"=>["Evolutionary Biology", "Medicine", "Molecular Biology"], "users"=>["Morgan N. Price", "Paramvir S. Dehal", "Adam P. Arkin"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0009490.g001", "stats"=>{"downloads"=>7, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Local_support_values_for_splits_found_by_PhyML_with_SPR_moves_and_or_FastTree_/529622", "title"=>"Local support values for splits found by PhyML with SPR moves and/or FastTree.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-03-10 02:40:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/859454"], "description"=>"<p>We ran RAxML with the fast convergence option. All values for COGs are averages over seven families. Log likelihoods for all topologies were computed with RAxML using and GTR or JTT. Global bootstrap values are from using the standard bootstrap with RAxML 7.0.4 (from <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0009490#pone.0009490-Stamatakis2\" target=\"_blank\">[11]</a>). SH-like local support values for RAxML's topology were computed with FastTree 2, the CAT approximation, and GTR or JTT.</p>", "links"=>[], "tags"=>["raxml", "fasttree", "well-supported"], "article_id"=>529921, "categories"=>["Evolutionary Biology", "Medicine", "Molecular Biology"], "users"=>["Morgan N. Price", "Paramvir S. Dehal", "Adam P. Arkin"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0009490.t003", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_RAxML_and_FastTree_s_log_likelihoods_and_the_agreement_of_FastTree_with_RAxML_s_well_supported_splits_for_large_genuine_alignments_/529921", "title"=>"Comparison of RAxML and FastTree's log likelihoods, and the agreement of FastTree with RAxML's well-supported splits, for large genuine alignments.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-03-10 02:45:21"}
  • {"files"=>["https://ndownloader.figshare.com/files/859428"], "description"=>"<p>For all topologies, the log likelihood was computed with RAxML 7, re-optimized branch lengths and model parameters, and the GTR+ or JTT+ models for 16S or COG, respectively. All differences between FastTree and other methods were statistically significant () except for the comparison with PhyML on 16S rRNAs (, paired test).</p>", "links"=>[], "tags"=>["log-likelihood", "alignments", "500"], "article_id"=>529887, "categories"=>["Evolutionary Biology", "Medicine", "Molecular Biology"], "users"=>["Morgan N. Price", "Paramvir S. Dehal", "Adam P. Arkin"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0009490.t002", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Average_log_likelihood_for_genuine_alignments_with_500_sequences_/529887", "title"=>"Average log-likelihood for genuine alignments with 500 sequences.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-03-10 02:44:47"}

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