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FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments
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BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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. CONCLUSIONS/SIGNIFICANCE: FastTree 2 allows the inference of maximum-likelihood phylogenies for huge alignments. FastTree 2 is freely available at http://www.microbesonline.org/fasttree.
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![Figure 1 Local support values for splits found by PhyML with SPR moves and/or FastTree. 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 [21] and SH-like [16], [17] local supports.](/paper-figures/8d86db71595b4c3189b248ede78bcc3f/fasttree-2-approximately-maximum-likelihood-trees-for-large-alignments-figure-1.jpg)
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“So far, these four programs have only been evaluated using simulated data (Guindon et al. 2010; Price et al. 2010; Liu et al. 2011), and empirical data sets with wide ranges of taxon numbers (e.g., up to 237,882 taxa in Price et al. [2010]) but relatively small numbers of genes (from ∼10 [Price et al. 2010; Liu et al. 2011; Chernomor et al. 2016] to ∼200 [Guindon et al. 2010; Money and Whelan 2012”
From Evaluating fast maximum likelihood-based phylogenetic programs using empirical phylogenomic data sets (2018) · cites this paper as Price et al. 2010
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“Thus, the validation process for our methods is centered around the comparison of phylogenetic trees estimated from the alignment with FastTree 2.1 (ref. 34).”
From Improving microbial phylogeny with citizen science within a mass-market video game (2025) · cites this paper as [34]
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“On the other hand, FastTree was found to be much faster than RAxML and PhyML but reported lower likelihood scores for data sets with both small and large numbers of sequences (Guindon et al. 2010; Price et al. 2010; Liu et al. 2011).”
From Evaluating fast maximum likelihood-based phylogenetic programs using empirical phylogenomic data sets (2018) · cites this paper as Price et al. 2010
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“As a tradeoff, FastTree generates less accurate tree estimates than SPR-based ML methods (Price et al. 2010).”
From Evaluating fast maximum likelihood-based phylogenetic programs using empirical phylogenomic data sets (2018) · cites this paper as Price et al. 2010
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“For example, the recently developed FastTree program can be orders of magnitude faster than either PhyML or RAxML/ExaML (Price et al. 2010).”
From Evaluating fast maximum likelihood-based phylogenetic programs using empirical phylogenomic data sets (2018) · cites this paper as Price et al. 2010
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Cites
The neighbor-joining method: a new method for reconstructing phylogenetic trees.
Saitou, N., & Nei, M. (1987) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a040454 · Cited by 59,959
CONFIDENCE LIMITS ON PHYLOGENIES: AN APPROACH USING THE BOOTSTRAP
Felsenstein, J. (1985) · Evolution · doi:10.1111/j.1558-5646.1985.tb00420.x · Cited by 44,791
DeLong, E. R., DeLong, D. M., & Clarke-Pearson, D. L. (1988) · Biometrics · doi:10.2307/2531595 · Cited by 22,649
Guindon, S., Dufayard, J.-F., Lefort, V., Anisimova, M., Hordijk, W., & Gascuel, O. (2010) · Systematic Biology · doi:10.1093/sysbio/syq010 · Cited by 18,376
A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood
Guindon, S., & Gascuel, O. (2003) · Systematic Biology · doi:10.1080/10635150390235520 · Cited by 16,923
RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models
Stamatakis, A. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl446 · Cited by 15,582
Evolutionary trees from DNA sequences: A maximum likelihood approach.
Felsenstein, J. (1981) · Journal of Molecular Evolution · doi:10.1007/bf01734359 · Cited by 14,571
Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB
DeSantis, T. Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E. L., Keller, K., Huber, T., Dalevi, D., Hu, P., & Andersen, G. L. (2006) · Applied and Environmental Microbiology · doi:10.1128/aem.03006-05 · Cited by 10,891
A Rapid Bootstrap Algorithm for the RAxML Web Servers
Stamatakis, A., Hoover, P., & Rougemont, J. (2008) · Systematic Biology · doi:10.1080/10635150802429642 · Cited by 7,028
FastTree: Computing Large Minimum Evolution Trees with Profiles instead of a Distance Matrix
Price, M. N., Dehal, P. S., & Arkin, A. P. (2009) · Molecular Biology and Evolution · doi:10.1093/molbev/msp077 · Cited by 5,602
Self-citation
Cited by
Sorted by citations
Guindon, S., Dufayard, J.-F., Lefort, V., Anisimova, M., Hordijk, W., & Gascuel, O. (2010) · Systematic Biology · doi:10.1093/sysbio/syq010 · Cited by 18,376
IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era
Minh, B. Q., Schmidt, H. A., Chernomor, O., Schrempf, D., Woodhams, M. D., von Haeseler, A., & Lanfear, R. (2020) · Molecular Biology and Evolution · doi:10.1093/molbev/msaa015 · Cited by 16,873
OrthoFinder: phylogenetic orthology inference for comparative genomics
Emms, D. M., & Kelly, S. (2019) · Genome Biology · doi:10.1186/s13059-019-1832-y · Cited by 7,676
Pfam: the protein families database
Finn, R. D., Bateman, A., Clements, J., Coggill, P., Eberhardt, R. Y., Eddy, S. R., Heger, A., Hetherington, K., Holm, L., Mistry, J., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1223 · Cited by 6,148
McDonald, D. T., Price, M. N., Goodrich, J. K., Nawrocki, E. P., DeSantis, T. Z., Probst, A. J., Andersen, G. L., Knight, R. D., & Hugenholtz, P. (2011) · The ISME Journal · doi:10.1038/ismej.2011.139 · Cited by 5,144
Self-citationGut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients
Gopalakrishnan, V., Spencer, C. N., Nezi, L., Reuben, A., Andrews, M. C., Karpinets, T. V., Prieto, P. A., Vicente, D., Hoffman, K., Wei, S. C., et al. (2018) · Science · doi:10.1126/science.aan4236 · Cited by 4,812
Cpf1 Is a Single RNA-Guided Endonuclease of a Class 2 CRISPR-Cas System
Zetsche, B., Gootenberg, J. S., Abudayyeh, O. O., Slaymaker, I. M., Makarova, K. S., Essletzbichler, P., Volz, S. E., Joung, J., van der Oost, J., Regev, A., et al. (2015) · Cell · doi:10.1016/j.cell.2015.09.038 · Cited by 4,761
RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference
Kozlov, A. M., Darriba, D., Flouri, T., Morel, B., & Stamatakis, A. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz305 · Cited by 4,425
AliView: a fast and lightweight alignment viewer and editor for large datasets
Larsson, A. O. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu531 · Cited by 3,773
Emms, D. M., & Kelly, S. (2015) · Genome Biology · doi:10.1186/s13059-015-0721-2 · Cited by 3,408
RDP4: Detection and analysis of recombination patterns in virus genomes
Martin, D. P., Murrell, B., Golden, M., Khoosal, A., & Muhire, B. M. (2015) · Virus Evolution · doi:10.1093/ve/vev003 · Cited by 3,338
Gut microbiota composition correlates with diet and health in the elderly
Claesson, M. J., Jeffery, I. B., Conde, S., Power, S. E., O’Connor, E. M., Cusack, S., Harris, H. M. B., Coakley, M., Lakshminarayanan, B., O’Sullivan, O., et al. (2012) · Nature · doi:10.1038/nature11319 · Cited by 3,314
Shifting the limits in wheat research and breeding using a fully annotated reference genome
Appels, R., Eversole, K., Stein, N., Feuillet, C., Keller, B., Rogers, J., Pozniak, C. J., Choulet, F., Distelfeld, A., Poland, J., et al. (2018) · Science · doi:10.1126/science.aar7191 · Cited by 3,183
Croucher, N. J., Page, A. J., Connor, T. R., Delaney, A. J., Keane, J. A., Bentley, S. D., Parkhill, J., & Harris, S. R. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1196 · Cited by 2,782
Dysfunction of the intestinal microbiome in inflammatory bowel disease and treatment
Morgan, X. C., Tickle, T. L., Sokol, H., Gevers, D., Devaney, K. L., Ward, D. V., Reyes, J. A., Shah, S. A., LeLeiko, N., Snapper, S. B., et al. (2012) · Genome Biology · doi:10.1186/gb-2012-13-9-r79 · Cited by 2,713
Structure and function of the global topsoil microbiome
Bahram, M., Hildebrand, F., Forslund, S. K., Anderson, J., Soudzilovskaia, N. A., van Bodegom, P. M., Bengtsson‐Palme, J., Anslan, S., Coelho, L. P., Harend, H., et al. (2018) · Nature · doi:10.1038/s41586-018-0386-6 · Cited by 2,638
Microbial diversity drives multifunctionality in terrestrial ecosystems
Delgado-Baquerizo, M., Maestre, F. T., Reich, P. B., Jeffries, T. C., Gaitan, J. J., Encinar, D., Berdugo, M., Campbell, C. D., & Singh, B. K. (2016) · Nature Communications · doi:10.1038/ncomms10541 · Cited by 2,624
Zhalnina, K., Louie, K., Hao, Z., Mansoori, N., da Rocha, U. N., Shi, S., Cho, H., Karaöz, U., Loqué, D., Bowen, B. P., et al. (2018) · Nature Microbiology · doi:10.1038/s41564-018-0129-3 · Cited by 2,481
ASTRAL-III: polynomial time species tree reconstruction from partially resolved gene trees
Zhang, C., Rabiee, M., Sayyari, E., & Mirarab, S. (2018) · BMC Bioinformatics · doi:10.1186/s12859-018-2129-y · Cited by 2,471
Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis
Johnson, J. S., Spakowicz, D. J., Hong, B., Petersen, L., Demkowicz, P. C., Chen, L., Leopold, S. R., Hanson, B., Agresta, H. O., Gerstein, M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-13036-1 · Cited by 2,457
Clustal Omega for making accurate alignments of many protein sequences
Sievers, F., & Higgins, D. G. (2018) · Protein Science · doi:10.1002/pro.3290 · Cited by 2,137
Huerta‐Cepas, J., Szklarczyk, D., Forslund, S. K., Cook, H., Heller, D., Walter, M. C., Rattei, T., Mende, D. R., Sunagawa, S., Kuhn, M., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1248 · Cited by 2,118
Medema, M. H., Blin, K., Cimermančič, P., de Jager, V., Zakrzewski, P., Fischbach, M. A., Weber, T., Takano, E., & Breitling, R. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr466 · Cited by 2,067
Expansion of intestinal Prevotella copri correlates with enhanced susceptibility to arthritis
Scher, J. U., Sczesnak, A., Longman, R. S., Segata, N., Ubeda, C., Bielski, C., Rostron, T., Cerundolo, V., Pamer, E. G., Abramson, S. B., et al. (2013) · eLife · doi:10.7554/elife.01202 · Cited by 2,047
One thousand plant transcriptomes and the phylogenomics of green plants
Initiative, O. T. P. T. (2019) · Nature · doi:10.1038/s41586-019-1693-2 · Cited by 1,734
Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa
Viana, R. P. E. S., Moyo, S. M., Amoako, D. G., Tegally, H., Scheepers, C., Althaus, C. L., Anyaneji, U. J., Bester, P. A., Boni, M. F., Chand, M., et al. (2022) · Nature · doi:10.1038/s41586-022-04411-y · Cited by 1,678
Treangen, T. J., Ondov, B., Koren, S., & Phillippy, A. M. (2014) · Genome biology · doi:10.1186/s13059-014-0524-x · Cited by 1,670
The shared antibiotic resistome of soil bacteria and human pathogens
Forsberg, K. J., Reyes, A., Wang, B., Selleck, E. M., Sommer, M. O. A., & Dantas, G. (2012) · Science · doi:10.1126/science.1220761 · Cited by 1,650
KBase: The United States Department of Energy Systems Biology Knowledgebase
(2018) · doi:10.1038/nbt.4163 · Cited by 1,624
Self-citationAntibiotics in early life alter the murine colonic microbiome and adiposity
Cho, I., Yamanishi, S., Cox, L., Methé, B. A., Zavadil, J., Li, K., Gao, Z., Mahana, D., Raju, K., Teitler, I., et al. (2012) · Nature · doi:10.1038/nature11400 · Cited by 1,613
Pasolli, E., Asnicar, F., Manara, S., Zolfo, M., Karcher, N., Armanini, F., Beghini, F., Manghi, P., Tett, A., Ghensi, P., et al. (2019) · Cell · doi:10.1016/j.cell.2019.01.001 · Cited by 1,591
Microbial co-occurrence relationships in the human microbiome
Faust, K., Sathirapongsasuti, J. F., Izard, J., Segata, N., Gevers, D., Raes, J., & Huttenhower, C. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002606 · Cited by 1,527
Real-time, portable genome sequencing for Ebola surveillance
Quick, J., Loman, N. J., Duraffour, S., Simpson, J. T., Severi, E., Cowley, L. A., Boré, J. A., Koundouno, F. R., Dudas, G., Mikhail, A. F. W., et al. (2016) · Nature · doi:10.1038/nature16996 · Cited by 1,479
Antibiotics, birth mode, and diet shape microbiome maturation during early life
Bokulich, N. A., Chung, J., Battaglia, T., Henderson, N., Jay, M., Li, H., D. Lieber, A., Wu, F., Perez-Perez, G. I., Chen, Y., et al. (2016) · Science Translational Medicine · doi:10.1126/scitranslmed.aad7121 · Cited by 1,469
Exercise and associated dietary extremes impact on gut microbial diversity
Clarke, S. F., Murphy, E. F., O'Sullivan, O., Lucey, A. J., Humphreys, M., Hogan, A., Hayes, P., O'Reilly, M., Jeffery, I. B., Wood-Martin, R., et al. (2014) · Gut · doi:10.1136/gutjnl-2013-306541 · Cited by 1,439
FUBAR: A Fast, Unconstrained Bayesian AppRoximation for Inferring Selection
Murrell, B., Moola, S., Mabona, A., Weighill, T., Sheward, D. J., Pond, S. L. K., & Scheffler, K. (2013) · Molecular Biology and Evolution · doi:10.1093/molbev/mst030 · Cited by 1,404
SNP-sites: rapid efficient extraction of SNPs from multi-FASTA alignments
Page, A. J., Taylor, B. E. W., Delaney, A. J., Soares, J., Seemann, T., Keane, J. A., & Harris, S. R. (2016) · Microbial Genomics · doi:10.1099/mgen.0.000056 · Cited by 1,403
UBCG: Up-to-date bacterial core gene set and pipeline for phylogenomic tree reconstruction
Na, S.-I., Kim, Y. O., Yoon, S.-H., Ha, S. M., Baek, I., & Chun, J. (2018) · The Journal of Microbiology · doi:10.1007/s12275-018-8014-6 · Cited by 1,371
Anaerobic oxidation of methane coupled to nitrate reduction in a novel archaeal lineage
Haroon, M. F., Hu, S., Shi, Y., Imelfort, M., Keller, J., Hugenholtz, P., Yuan, Z., & Tyson, G. W. (2013) · Nature · doi:10.1038/nature12375 · Cited by 1,364
Functional overlap of the Arabidopsis leaf and root microbiota
Bai, Y., Müller, D. B., Srinivas, G., Garrido‐Oter, R., Potthoff, E., Rott, M., Dombrowski, N., Münch, P. C., Spaepen, S., Remus‐Emsermann, M. N. P., et al. (2015) · Nature · doi:10.1038/nature16192 · Cited by 1,359
Olson, R., Assaf, R., Brettin, T. S., Conrad, N. R., Cucinell, C. A., Davis, J. J., Dempsey, D. M., Dickerman, A., Dietrich, E. M., Kenyon, R. W., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac1003 · Cited by 1,342
Salt-responsive gut commensal modulates TH17 axis and disease
Wilck, N., Matus, M. G., Kearney, S. M., Olesen, S. W., Forslund, K., Bartolomaeus, H., Haase, S., Mähler, A., Balogh, A., Markó, L., et al. (2017) · Nature · doi:10.1038/nature24628 · Cited by 1,310
Culturing of ‘unculturable’ human microbiota reveals novel taxa and extensive sporulation
Browne, H. P., Forster, S. C., Anonye, B. O., Kumar, N., Neville, B. A., Stares, M. D., Goulding, D., & Lawley, T. D. (2016) · Nature · doi:10.1038/nature17645 · Cited by 1,299
Edgar, R. C. (2022) · Nature Communications · doi:10.1038/s41467-022-34630-w · Cited by 1,287
Albertsen, M., Hugenholtz, P., Skarshewski, A., Nielsen, K. L., Tyson, G. W., & Nielsen, P. H. (2013) · Nature Biotechnology · doi:10.1038/nbt.2579 · Cited by 1,259
Unusual biology across a group comprising more than 15% of domain Bacteria
Brown, C. T., Hug, L. A., Thomas, B. C., Sharon, I., Castelle, C. J., Singh, A., Wilkins, M. J., Wrighton, K. C., Williams, K. H., & Banfield, J. F. (2015) · Nature · doi:10.1038/nature14486 · Cited by 1,216
Discovery and Functional Characterization of Diverse Class 2 CRISPR-Cas Systems
Shmakov, S., Abudayyeh, O. O., Makarova, K. S., Wolf, Y. I., Gootenberg, J. S., Semenova, E., Minakhin, L., Joung, J., Konermann, S., Severinov, K., et al. (2015) · Molecular Cell · doi:10.1016/j.molcel.2015.10.008 · Cited by 1,209
Neonatal gut microbiota associates with childhood multisensitized atopy and T cell differentiation
Fujimura, K. E., Sitarik, A. R., Havstad, S. L., Lin, D. L., Levan, S., Fadrosh, D. W., Panzer, A. R., LaMere, B. J., Rackaityte, E., Lukacs, N. W., et al. (2016) · Nature Medicine · doi:10.1038/nm.4176 · Cited by 1,198
TreeTime: Maximum-likelihood phylodynamic analysis
Sagulenko, P., Puller, V., & Neher, R. A. (2017) · Virus Evolution · doi:10.1093/ve/vex042 · Cited by 1,185
Identification of mobile genetic elements with geNomad
Camargo, A. P., Roux, S., Schulz, F., Babinski, M., Xu, Y., Hu, B., Chain, P., Nayfach, S., & Kyrpides, N. C. (2023) · Nature Biotechnology · doi:10.1038/s41587-023-01953-y · Cited by 1,160
Topographical Continuity of Bacterial Populations in the Healthy Human Respiratory Tract
Charlson, E. S., Bittinger, K., Haas, A. R., Fitzgerald, A. S., Frank, I., Yadav, A., Bushman, F. D., & Collman, R. G. (2011) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201104-0655oc · Cited by 1,144
Stoddard, S. F., Smith, B. J., Hein, R., Roller, B. R. K., & Schmidt, T. M. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1201 · Cited by 1,142
Assignment of epidemiological lineages in an emerging pandemic using the pangolin tool
O’Toole, Á., Scher, E., Underwood, A. P., Jackson, B., Hill, V., McCrone, J. T., Colquhoun, R., Ruis, C., Abudahab, K., Taylor, B. E. W., et al. (2021) · Virus Evolution · doi:10.1093/ve/veab064 · Cited by 1,082
Soil pH mediates the balance between stochastic and deterministic assembly of bacteria
Tripathi, B. M., Stegen, J., Kim, M., Dong, K., Adams, J. M., & Lee, Y. K. (2018) · The ISME Journal · doi:10.1038/s41396-018-0082-4 · Cited by 1,070
Matsen, F. A., IV, Kodner, R. B., & Armbrust, E. V. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-538 · Cited by 1,058
Adeolu, M., Alnajar, S., Naushad, S., & Gupta, R. S. (2016) · INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY · doi:10.1099/ijsem.0.001485 · Cited by 1,051
Microbial biogeography of wine grapes is conditioned by cultivar, vintage, and climate
Bokulich, N. A., Thorngate, J. H., Richardson, P. M., & Mills, D. A. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1317377110 · Cited by 1,041
New evidences on the altered gut microbiota in autism spectrum disorders
Strati, F., Cavalieri, D., Albanese, D., De Felice, C., Donati, C., Hayek, J., Jousson, O., Leoncini, S., Renzi, D., Calabrò, A., et al. (2017) · Microbiome · doi:10.1186/s40168-017-0242-1 · Cited by 1,040
Thomas, A. M., Manghi, P., Asnicar, F., Pasolli, E., Armanini, F., Zolfo, M., Beghini, F., Manara, S., Karcher, N., Pozzi, C., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0405-7 · Cited by 1,030
Pan-Genome of Wild and Cultivated Soybeans
Liu, Y., Du, H., Li, P., Shen, Y., Peng, H., Liu, S., Zhou, G., Zhang, H., Liu, Z., Shi, M., et al. (2020) · Cell · doi:10.1016/j.cell.2020.05.023 · Cited by 1,010
PlantTFDB 3.0: a portal for the functional and evolutionary study of plant transcription factors
Jin, J., Zhang, H., Kong, L., Gao, G., & Luo, J. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1016 · Cited by 976
Solving the Problem of Comparing Whole Bacterial Genomes across Different Sequencing Platforms
Kaas, R. S., Leekitcharoenphon, P., Aarestrup, F. M., & Lund, O. (2014) · PLoS ONE · doi:10.1371/journal.pone.0104984 · Cited by 958
NGPhylogeny.fr: new generation phylogenetic services for non-specialists
Lemoine, F., Correia, D., Lefort, V., Doppelt‐Azeroual, O., Mareuil, F., Cohen‐Boulakia, S., & Gascuel, O. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz303 · Cited by 951
Mirarab, S., & Warnow, T. J. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv234 · Cited by 945
Leone, V., Gibbons, S. M., Martinez, K., Hutchison, A. L., Huang, E. Y., Cham, C. M., Pierre, J. F., Heneghan, A. F., Nadimpalli, A., Hubert, N., et al. (2015) · Cell Host & Microbe · doi:10.1016/j.chom.2015.03.006 · Cited by 921
The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities
Davis, J. J., Wattam, A. R., Aziz, R. K., Brettin, T. S., Butler, R. M., Butler, R., Chlenski, P., Conrad, N. R., Dickerman, A. W., Dietrich, E. M., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz943 · Cited by 902
Global diversity and biogeography of bacterial communities in wastewater treatment plants
Wu, L., Ning, D., Zhang, B., Li, Y., Zhang, P., Shan, X., Zhang, Q., Brown, M. R., Li, Z., Nostrand, J. D. V., et al. (2019) · Nature Microbiology · doi:10.1038/s41564-019-0426-5 · Cited by 899
ClonalFrameML: Efficient Inference of Recombination in Whole Bacterial Genomes
Didelot, X., & Wilson, D. J. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004041 · Cited by 896
Antibiotic Resistome and Its Association with Bacterial Communities during Sewage Sludge Composting
Su, J., Wei, B., Ouyang, W.-Y., Huang, F.-Y., Zhao, Y., Xu, H., & Zhu, Y. (2015) · Environmental Science & Technology · doi:10.1021/acs.est.5b01012 · Cited by 893
A genomic catalog of Earth’s microbiomes
Nayfach, S., Roux, S., Seshadri, R., Udwary, D., Varghese, N. J., Schulz, F., Wu, D., Páez-Espino, D., Chen, I.-M. A., Huntemann, M., et al. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0718-6 · Cited by 890
Self-citationWang, Y., Coleman‐Derr, D., Chen, G., & Gu, Y. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv487 · Cited by 887
Asnicar, F., Thomas, A. M., Beghini, F., Mengoni, C., Manara, S., Manghi, P., Zhu, Q., Bolzan, M., Cumbo, F., May, U., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-16366-7 · Cited by 869
Fast Coalescent-Based Computation of Local Branch Support from Quartet Frequencies
Sayyari, E., & Mirarab, S. (2016) · Molecular Biology and Evolution · doi:10.1093/molbev/msw079 · Cited by 868
Ecogenomics and potential biogeochemical impacts of globally abundant ocean viruses
Roux, S., Brum, J. R., Dutilh, B. E., Sunagawa, S., Duhaime, M. B., Loy, A., Poulos, B. T., Solonenko, N., Lara, E., Poulain, J., et al. (2016) · Nature · doi:10.1038/nature19366 · Cited by 863
PhyloPhlAn is a new method for improved phylogenetic and taxonomic placement of microbes
Segata, N., Börnigen, D., Morgan, X. C., & Huttenhower, C. (2013) · Nature Communications · doi:10.1038/ncomms3304 · Cited by 844
Mathers, T. C., Chen, Y., Kaithakottil, G., Legeai, F., Mugford, S. T., Bâa-Puyoulet, P., Bretaudeau, A., Clavijo, B., Colella, S., Collin, O., et al. (2017) · Genome biology · doi:10.1186/s13059-016-1145-3 · Cited by 841
Zallot, R., Oberg, N., & Gerlt, J. A. (2019) · Biochemistry · doi:10.1021/acs.biochem.9b00735 · Cited by 806
Wemheuer, F., Taylor, J. A., Daniel, R., Johnston, E. L., Meinicke, P., Thomas, T., & Wemheuer, B. (2020) · Environmental Microbiome · doi:10.1186/s40793-020-00358-7 · Cited by 804
Barnes, C. O., West, A. P., Huey-Tubman, K. E., Hoffmann, M. A. G., Sharaf, N. G., Hoffman, P. R., Koranda, N., Gristick, H. B., Gaebler, C., Muecksch, F., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.025 · Cited by 795
Chandler, J., Lang, J., Bhatnagar, S., Eisen, J. A., & Kopp, A. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002272 · Cited by 788
SARS-CoV-2 Omicron is an immune escape variant with an altered cell entry pathway
Willett, B. J., Grove, J., MacLean, O. A., Wilkie, C., De Lorenzo, G., Furnon, W., Cantoni, D., Scott, S., Logan, N., Ashraf, S., et al. (2022) · Nature Microbiology · doi:10.1038/s41564-022-01143-7 · Cited by 785
Virus taxonomy in the age of metagenomics
Peter Simmonds, K., Adams, M., Benkő, M., Breitbart, M., Brister, J. R., Carstens, E. B., Davison, A. J., Delwart, E., Gorbalenya, A. E., Harrach, B., et al. (2017) · Nature Reviews Microbiology · doi:10.1038/nrmicro.2016.177 · Cited by 760
Using QIIME to Analyze 16S rRNA Gene Sequences from Microbial Communities
Kuczynski, J., Stombaugh, J., Walters, W. A., González, A., Caporaso, J. G., & Knight, R. D. (2011) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi1007s36 · Cited by 750
Long-term benefit of microbiota transfer therapy on autism symptoms and gut microbiota
Kang, D.-W., Adams, J. B., Coleman, D. M., Pollard, E. L., Maldonado, J., McDonough-Means, S., Caporaso, J. G., & Krajmalnik-Brown, R. (2019) · Scientific Reports · doi:10.1038/s41598-019-42183-0 · Cited by 749
Understanding and exploiting plant beneficial microbes
Finkel, O. M., Castrillo, G., Paredes, S. H., Salas-González, I., & Dangl, J. L. (2017) · Current Opinion in Plant Biology · doi:10.1016/j.pbi.2017.04.018 · Cited by 749
Wang, H., Zhang, Y., Huang, B., Deng, W., Quan, Y., Wang, W., Xu, W., Zhao, Y., Li, N., Zhang, J., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.008 · Cited by 748
Host genetic variation impacts microbiome composition across human body sites
Blekhman, R., Goodrich, J. K., Huang, K., Sun, Q., Bukowski, R., Bell, J. T., Spector, T. D., Keinan, A., Ley, R. E., Gevers, D., et al. (2015) · Genome Biology · doi:10.1186/s13059-015-0759-1 · Cited by 745
New insights from uncultivated genomes of the global human gut microbiome
Nayfach, S., Shi, Z. J., Seshadri, R., Pollard, K. S., & Kyrpides, N. C. (2019) · Nature · doi:10.1038/s41586-019-1058-x · Cited by 737
Renewing Felsenstein’s phylogenetic bootstrap in the era of big data
Lemoine, F., Entfellner, J.-B. D., Wilkinson, E., Correia, D., Felipe, M. D., de Oliveira, T., & Gascuel, O. (2018) · Nature · doi:10.1038/s41586-018-0043-0 · Cited by 733
Experimental and analytical tools for studying the human microbiome
Kuczynski, J., Lauber, C. L., Walters, W. A., Parfrey, L. W., Clemente, J. C., Gevers, D., & Knight, R. D. (2011) · Nature Reviews Genetics · doi:10.1038/nrg3129 · Cited by 729
Meehan, C. J., & Beiko, R. G. (2014) · Genome Biology and Evolution · doi:10.1093/gbe/evu050 · Cited by 724
Temperature mediates continental-scale diversity of microbes in forest soils
Zhou, J. Z., Deng, Y., Shen, L., Wen, C., Yan, Q., Ning, D., Qin, Y., Xue, K., Wu, L., He, Z., et al. (2016) · Nature Communications · doi:10.1038/ncomms12083 · Cited by 717
Schroeder, B. O., Birchenough, G. M. H., Ståhlman, M., Arike, L., Johansson, M. E. V., Hansson, G. C., & Bäckhed, F. (2018) · Cell Host & Microbe · doi:10.1016/j.chom.2017.11.004 · Cited by 713
Developmental pathway for potent V1V2-directed HIV-neutralizing antibodies
Doria‐Rose, N. A., Schramm, C. A., Gorman, J., Moore, P. L., Bhiman, J. N., DeKosky, B. J., Ernandes, M. J., Georgiev, I. S., Kim, H. J., Pancera, M., et al. (2014) · Nature · doi:10.1038/nature13036 · Cited by 713
Deschasaux, M., Bouter, K. E., Prodan, A., Levin, E., Groen, A. K., Herrema, H., Tremaroli, V., Bakker, G. J., Attaye, I., Pinto-Sietsma, S.-J., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0160-1 · Cited by 695
Leung, K., Shum, M. H., Leung, G. M., Lam, T. T., & Wu, J. T. (2021) · Eurosurveillance · doi:10.2807/1560-7917.es.2020.26.1.2002106 · Cited by 694
Ormerod, K. L., Wood, D., Lachner, N., Gellatly, S. L., Daly, J. N., Parsons, J. D., Dal’Molin, C. G. D. O., Palfreyman, R. W., Nielsen, L. K., Cooper, M. A., et al. (2016) · Microbiome · doi:10.1186/s40168-016-0181-2 · Cited by 691
Using QIIME to Analyze 16S rRNA Gene Sequences from Microbial Communities
Kuczynski, J., Stombaugh, J., Walters, W. A., González, A., Caporaso, J. G., & Knight, R. D. (2012) · Current Protocols in Microbiology · doi:10.1002/9780471729259.mc01e05s27 · Cited by 676
Gut microbiome pattern reflects healthy ageing and predicts survival in humans
Wilmanski, T., Diener, C., Rappaport, N., Patwardhan, S., Wiedrick, J., Lapidus, J., Earls, J. C., Zimmer, A., Glusman, G., Robinson, M., et al. (2021) · Nature Metabolism · doi:10.1038/s42255-021-00348-0 · Cited by 675
Metadata
- Authors
- Price, M. N., Dehal, P. S., & Arkin, A. P.
- Affiliations
- Lawrence Berkeley National Laboratory (US)
- Corresponding author
- Price, Morgan N.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2010-03-10
- Volume
- 5
- Issue
- 3
- Pages
- e9490
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC2835736
- OpenAlex
- W2031611770
- Cited by
- 14,894
- References
- 37
- Citations by year
- 2026: 1298 · 2025: 1543 · 2024: 1657 · 2023: 1486 · 2022: 1676 · 2021: 1651 · 2020: 1363 · 2019: 1013 · 2018: 776 · 2017: 686 · 2016: 521 · 2015: 415 · 2014: 309 · 2013: 256 · 2012: 133
- FWCI
- 63.80
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- eScholarship (California Digital Library) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- Figshare (submittedVersion, cc-by)
- Funders
- U.S. Department of Energy (-AC02-05CH11231, 05CH11231, DE AC02 05CH11231, DE-AC02-)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fractal and DNA sequence analysis
- Keywords
- phylogenetic inference, maximum likelihood phylogeny, nearest neighbor interchange, cat model, 16S rRNA, phylogenetic accuracy, scalability
- MeSH terms
- Algorithms, Animals, Computers, Data Interpretation, Statistical, Genetic Techniques, Humans, Models, Genetic, Phylogeny, RNA, Ribosomal, 16S, Software, Likelihood Functions, Sequence Alignment, Databases, Protein
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