4.7 Article

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

Journal

BIOINFORMATICS
Volume 38, Issue 23, Pages 5315-5316

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btac672

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Funding

  1. UQ Strategic Funding
  2. Australian Research Council Laureate Fellowship [FL150100038]

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This study presents an updated version of GTDB-Tk that uses a divide-and-conquer approach to reduce memory requirements while minimizing classification impact.
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 (similar to 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.

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