The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database
Open accessAbstract
Summary: The Genome Taxonomy Database Toolkit (GTDB-Tk) provides objective taxonomic assignments for bacterial and archaeal genomes based on the GTDB. GTDB-Tk is computationally efficient and able to classify thousands of draft genomes in parallel. Here we demonstrate the accuracy of the GTDB-Tk taxonomic assignments by evaluating its performance on a phylogenetically diverse set of 10 156 bacterial and archaeal metagenome-assembled genomes. Availability and implementation: GTDB-Tk is implemented in Python and licenced under the GNU General Public Licence v3.0. Source code and documentation are available at: https://github.com/ecogenomics/gtdbtk. Supplementary information: Supplementary data are available at Bioinformatics online.
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Accelerated Profile HMM Searches
Eddy, S. R. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002195 · Cited by 6,975
High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries
Jain, C., Rodriguez-R, L. M., Phillippy, A. M., Konstantinidis, K. T., & Aluru, S. (2018) · Nature Communications · doi:10.1038/s41467-018-07641-9 · Cited by 5,748
Research works printed but not linked: 17
- Anantharaman, 2016, Thousands of microbial genomes shed light on interconnected biogeochemical processes in an aquifer system, Nat. Commun, 7, 13219, 10.1038/ncomms13219 · DOI · Paper page
- Arkin, 2018, KBase: the United States Department of Energy Systems Biology Knowledgebase, Nat. Biotechnol, 36, 566, 10.1038/nbt.4163 · doi:10.1038/nbt.4163
- Bowers, 2017, Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea, Nat. Biotechnol, 35, 725, 10.1038/nbt.3893 · DOI · Paper page
- Coil, 2019, Genomes from bacteria associated with the canine oral cavity: a test case for automated genome-based taxonomic assignment, PLoS One, 14, e0214354, 10.1371/journal.pone.0214354 · DOI
- Federhen, 2015, Type material in the NCBI Taxonomy Database, Nucleic Acids Res, 43, D1086, 10.1093/nar/gku1127 · DOI · Paper page
- Godfray, 2002, Challenges for taxonomy, Nature, 417, 17, 10.1038/417017a · DOI · Paper page
- Hyatt, 2010, Prodigal: prokaryotic gene recognition and translation initiation site identification, BMC Bioinformatics, 11, 119, 10.1186/1471-2105-11-119 · DOI · Paper page
- Kitts, 2016, Assembly: a resource for assembled genomes at NCBI, Nucleic Acids Res, 44, D73, 10.1093/nar/gkv1226 · DOI · Paper page
- Konstantinidis, 2005, Genomic insights that advance the species definition for prokaryotes, Proc. Natl. Acad. Sci. USA, 102, 2567, 10.1073/pnas.0409727102 · DOI · Paper page
- Matsen, 2010, pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree, BMC Bioinformatics, 11, 538, 10.1186/1471-2105-11-538 · DOI · Paper page
- Nabhan, 2012, The impact of taxon sampling on phylogenetic inference: a review of two decades of controversy, Brief. Bioinform, 13, 122, 10.1093/bib/bbr014 · DOI · Paper page
- Parks, 2017, Recovery of nearly 8, 000 metagenome-assembled genomes substantially expands the tree of life, Nat. Microbiol, 2, 1533, 10.1038/s41564-017-0012-7 · DOI · Paper page
- Parks, 2018, A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life, Nat. Biotechnol, 36, 996, 10.1038/nbt.4229 · DOI · Paper page
- Parks, 2019, Selection of representative genomes for 24, 706 bacterial and archaeal species clusters provide a complete genome-based taxonomy, bioRxiv, 771964
- Pasolli, 2019, Extensive unexplored human microbiome diversity revealed by over 150, 000 genomes from metagenomes spanning age, geography, and lifestyle, Cell, 176, 649, 10.1016/j.cell.2019.01.001 · DOI · Paper page
- Rodriguez-R, 2018, The Microbial Genomes Atlas (MiGA) webserver: taxonomic and gene diversity analysis of archaea and bacteria at the whole genome level, Nucleic Acids Res, 46, W282, 10.1093/nar/gky467 · DOI · Paper page
- Segata, 2013, PhyloPhlAn is a new method for improved phylogenetic and taxonomic placement of microbes, Nat. Commun, 4, 2304, 10.1038/ncomms3304 · DOI · Paper page
Cited by
Parks, D. H., Chuvochina, M., Rinke, C., Mussig, A. J., Chaumeil, P.-A., & Hugenholtz, P. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkab776 · Cited by 2,402
Self-citationBeghini, F., McIver, L. J., Blanco-Míguez, A., Dubois, L., Asnicar, F., Maharjan, S., Mailyan, A., Manghi, P., Scholz, M., Thomas, A. M., et al. (2021) · eLife · doi:10.7554/elife.65088 · Cited by 2,303
Blanco-Míguez, A., Beghini, F., Cumbo, F., McIver, L. J., Thompson, K. N., Zolfo, M., Manghi, P., Dubois, L., Huang, K. D., Thomas, A. M., et al. (2023) · Nature Biotechnology · doi:10.1038/s41587-023-01688-w · Cited by 1,442
A unified catalog of 204,938 reference genomes from the human gut microbiome
Almeida, A., Nayfach, S., Boland, M., Strozzi, F., Beracochea, M., Shi, Z. J., Pollard, K. S., Sakharova, E., Parks, D. H., Hugenholtz, P., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-020-0603-3 · Cited by 1,367
Self-citationMetagenomic compendium of 189,680 DNA viruses from the human gut microbiome
Nayfach, S., Páez-Espino, D., Call, L., Low, S. J., Sberro, H., Ivanova, N. N., Proal, A. D., Fischbach, M. A., Bhatt, A. S., Hugenholtz, P., et al. (2021) · Nature Microbiology · doi:10.1038/s41564-021-00928-6 · Cited by 580
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Metadata
- Authors
- Chaumeil, P.-A., Mussig, A. J., Hugenholtz, P., & Parks, D. H.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2019-11-15
- Volume
- 36
- Issue
- 6
- Pages
- 1925-1927
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2986925300
- Cited by
- 5,259
- References
- 2
- FWCI
- 109.64
- Type
- journal article
- Language
- en
- Open access
- hybrid
- Funders
- Australian Research Council Laureate Fellowship (FL150100038)
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