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October 7, 2022BioinformaticsOpen Access

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

Pierre-Alain Chaumeil Aaron J. Mussig Philip Hugenholtz Donovan H. Parks

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Key Points

The objective is to enhance classification efficiency in genomic studies using the Genome Taxonomy Database.
Introduced GTDB-Tk v2 for classifying genomes
Optimized algorithms for better memory management
Provided supplementary data for additional insights
Demonstrated significant improvements in memory usage compared to previous versions
Achieved faster classification times without loss of accuracy
Supported by supplementary data available at Bioinformatics online

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Implication

Demonstrates improved classification with memory efficiency using GTDB-Tk v2, indicating potential for broader data usage.

Abstract

Supplementary data are available at Bioinformatics online.

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Cite This Study

Chaumeil et al. (2022) studied this question.

synapsesocial.com/papers/69d6f4da733a2b54c8aa8749 https://doi.org/10.1093/bioinformatics/btac672

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Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1GTDB: an ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomyOriginal Research · 2021 · 2,398 citations
2Taxonize-gb: A tool for filtering GenBank non-redundant databases based on taxonomy2024 · 1 citations
3TaxTriage: An Open-Source Metagenomic Sequencing Data Analysis Pipeline Enabling Putative Pathogen DetectionOriginal Research · 2026 · 1 citations
4Putative genome contamination has minimal impact on the GTDB taxonomy2024 · 7 citations
5Application and Comparison of Machine Learning and Database-Based Methods in Taxonomic Classification of High-Throughput Sequencing Data2024 · 27 citations

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