# GTDB-Tk v2: memory friendly classification with the genome taxonomy database

“GTDB-Tk v2: memory friendly classification with the genome taxonomy database” (2022), by Pierre-Alain Chaumeil et al. Genetics and Biochemistry research paper. Original abstract below, unchanged. A free PDF is available.

- Authors: Pierre-Alain Chaumeil, Aaron James Mussig, Philip Hugenholtz, Donovan H. Parks
- Published: October 7, 2022
- Field: Genetics and Biochemistry
- DOI: https://doi.org/10.1093/bioinformatics/btac672
- Free PDF: https://www.biorxiv.org/content/biorxiv/early/2022/07/22/2022.07.11.499641.full.pdf

## 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.

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