{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Chaumeil PA"],"funding":["UQ Strategic Funding and Australian Research Council Laureate Fellowship"],"pagination":["5315-5316"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9710552"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["38(23)"],"pubmed_abstract":["<h4>Summary</h4>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.<h4>Availability and implementation</h4>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.<h4>Supplementary information</h4>Supplementary data are available at Bioinformatics online."],"journal":["Bioinformatics (Oxford, England)"],"pubmed_title":["GTDB-Tk v2: memory friendly classification with the genome taxonomy database."],"pmcid":["PMC9710552"],"funding_grant_id":["FL150100038"],"pubmed_authors":["Parks DH","Mussig AJ","Hugenholtz P","Chaumeil PA"],"additional_accession":[]},"is_claimable":false,"name":"GTDB-Tk v2: memory friendly classification with the genome taxonomy database.","description":"<h4>Summary</h4>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.<h4>Availability and implementation</h4>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.<h4>Supplementary information</h4>Supplementary data are available at Bioinformatics online.","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Nov","modification":"2026-05-05T02:50:50.285Z","creation":"2025-04-06T13:59:20.466Z"},"accession":"S-EPMC9710552","cross_references":{"pubmed":["36218463"],"doi":["10.1093/bioinformatics/btac672"]}}