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

Chaumeil, Pierre-Alain ; Mussig, Aaron J ; Hugenholtz, Philip ; Parks, Donovan H Borgwardt, Karsten

Bioinformatics (Oxford, England), 2022-11, Vol.38 (23), p.5315-5316 [Periódico revisado por pares]

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Título:
GTDB-Tk v2: memory friendly classification with the genome taxonomy database
Autor: Chaumeil, Pierre-Alain ; Mussig, Aaron J ; Hugenholtz, Philip ; Parks, Donovan H
Borgwardt, Karsten
Assuntos: Applications Note ; Documentation ; Software
É parte de: Bioinformatics (Oxford, England), 2022-11, Vol.38 (23), p.5315-5316
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Descrição: 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.
Editor: England: Oxford University Press
Idioma: Inglês

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