GTDB-Tk v2: memory friendly classification with the genome taxonomy database
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ID: 297039
2022
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Abstract
Abstract Summary The Genome Taxonomy Database (GTDB) and associated taxonomic classification toolkit (GTDB-Tk) have been widely adopted by the microbiology community. However, the growing size of the GTDB bacterial reference tree has resulted in GTDB-Tk requiring substantial amounts of memory (∼320 GB) which limits its adoption and ease of use. Here, we present an update to GTDB-Tk that uses a divide-and-conquer approach where user genomes are initially placed into a bacterial reference tree with family-level representatives followed by placement into an appropriate class-level subtree comprising species representatives. This substantially reduces the memory requirements of GTDB-Tk while having minimal impact on classification. 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.
| Reference Key |
openalex_W4304481015
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|---|---|
| Authors | Pierre-Alain Chaumeil, Aaron J. Mussig, Philip Hugenholtz, Donovan H. Parks |
| Journal | BMC Bioinformatics |
| Year | 2022 |
| DOI |
10.1093/bioinformatics/btac672
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| URL | |
| Keywords | Keywords not found |
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