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

• Author: Chaumeil, Pierre-Alain ; Mussig, Aaron J ; Hugenholtz, Philip ; Parks, Donovan H
• Borgwardt, Karsten
• Subjects: Applications Note ; Documentation ; Software
• Is Part Of: Bioinformatics (Oxford, England), 2022-11, Vol.38 (23), p.5315-5316
• Description: 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. 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 data are available at Bioinformatics online.
  
• Publisher: England: Oxford University Press
  
• Language: English
  
• Identifier: ISSN: 1367-4803
  EISSN: 1367-4811
  DOI: 10.1093/bioinformatics/btac672
  PMID: 36218463
  
• Source: Journals@Ovid Open Access Journal Collection Rolling
  GFMER Free Medical Journals
  MEDLINE
  PubMed Central