A toolkit for assigning objective taxonomic classifications to bacterial and archaeal genomes.
Project description
GTDB-Tk
GTDB-Tk is a software toolkit for assigning objective taxonomic classifications to bacterial and archaeal genomes based on the Genome Database Taxonomy GTDB. It is designed to work with recent advances that allow hundreds or thousands of metagenome-assembled genomes (MAGs) to be obtained directly from environmental samples. It can also be applied to isolate and single-cell genomes. The GTDB-Tk is open source and released under the GNU General Public License (Version 3).
Notifications about GTDB-Tk releases will be available through the GTDB Twitter account (https://twitter.com/ace_gtdb).
Please post questions and issues related to GTDB-Tk on the Issues section of the GitHub repository. Questions related to the GTDB should be sent to the GTDB team.
Documentation
https://ecogenomics.github.io/GTDBTk/
References
GTDB-Tk is described in:
- Chaumeil PA, et al. 2019. GTDB-Tk: A toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics, btz848.
The Genome Taxonomy Database (GTDB) is described in:
- Parks DH, et al. 2019. Selection of representative genomes for 24,706 bacterial and archaeal species clusters provide a complete genome-based taxonomy. bioRxiv, https://doi.org/10.1101/771964.
- Parks DH, et al. 2018. A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nat. Biotechnol., http://dx.doi.org/10.1038/nbt.4229.
We strongly encourage you to cite the following 3rd party dependencies:
- Matsen FA, et al. 2010. pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree. BMC Bioinformatics, 11:538.
- Jain C, et al. 2019. High-throughput ANI Analysis of 90K Prokaryotic Genomes Reveals Clear Species Boundaries. Nat. Communications, doi: 10.1038/s41467-018-07641-9.
- Hyatt D, et al. 2010. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics, 11:119. doi: 10.1186/1471-2105-11-119.
- Price MN, et al. 2010. FastTree 2 - Approximately Maximum-Likelihood Trees for Large Alignments. PLoS One, 5, e9490.
- Eddy SR. 2011. Accelerated profile HMM searches. PLOS Comp. Biol., 7:e1002195.
- Ondov BD, et al. 2016. Mash: fast genome and metagenome distance estimation using MinHash. Genome Biol 17, 132. doi: doi: 10.1186/s13059-016-0997-x.
Copyright
Copyright 2017 Pierre-Alain Chaumeil. See LICENSE for further details.
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