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. 2022 Nov 30;38(23):5315-5316.
doi: 10.1093/bioinformatics/btac672.

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

Pierre-Alain Chaumeil  1   2 , Aaron J Mussig  1 , Philip Hugenholtz  1 , Donovan H Parks  1
Affiliations

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

Pierre-Alain Chaumeil et al. Bioinformatics. .

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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References

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