ArticleScientific data2024
Benchmarking bacterial taxonomic classification using nanopore metagenomics data of several mock communities.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- The Biotechnological Applications of Marine Bacteria.Biology · 2026Review
- Urinary microbiome in renal transplant patients with BK polyomavirus reactivation.Journal of medical microbiology · 2026Article
- Shifts in Rhizosphere Bacterial Community Composition and Predicted Functional Potential Associated with Impatiens parviflora Invasion in Temperate Forest.Microbial ecology · 2026Article
- A review of computational approaches for metagenomics by long-read sequencing.Science China. Life sciences · 2026Review
- SquiDBase: a community resource of raw nanopore data from microbes.NAR genomics and bioinformatics · 2026Article
- Filtering for truth: high-precision taxonomic classification in nanopore shotgun metagenomics data through a KMA-based bioinformatic pipeline (KAPTAIN).BMC genomics · 2026Article
- 2Pipe starts with a question: matching you with the correct pipeline for MAG reconstruction.mSystems · 2026Review
- Age-specific early-life gut microbiome associations with eczema and food allergies during early immune development.Frontiers in microbiomes · 2026Article
- Agentic AI for trustworthy synthetic microbial genomics: a perspective on generation, validation, and governance.Frontiers in bioinformatics · 2026Article
- Adaptation without Dominance in Pseudomonas syringae Pathovars.Microbial ecology · 2025Article
- Detection ofFood chemistry. Molecular sciences · 2025Article
- Real-time analysis and visualization of nanopore metagenomic samples with MARTi.Genome research · 2025Article
- Computational Metagenomics: State of the Art.International journal of molecular sciences · 2025Review
- Advancing metagenomic classification with NABAS+: a novel alignment-based approach.NAR genomics and bioinformatics · 2025Article
- Article
- Rapid identification platform of spores based on Raman spectroscopy.Food chemistry: X · 2025Article
- Leveraging artificial intelligence community analytics and nanopore metagenomic surveillance to monitor early enteropathogen outbreaks.Frontiers in public health · 2025Article
- Multi-platform metagenomic characterization of the microbial community during spontaneous cacao fermentation.Frontiers in bioengineering and biotechnology · 2025Article
- Overcoming challenges in metagenomic AMR surveillance with nanopore sequencing: a case study on fluoroquinolone resistance.Frontiers in microbiology · 2025Article
- The integral role of the Black Soldier fly,Frontiers in microbiomes · 2025Review
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Taxonomic classification is crucial in identifying organisms within diverse microbial communities when using metagenomics shotgun sequencing. While second-generation Illumina sequencing still dominates, third-generation nanopore sequencing promises improved classification through longer reads. However, extensive benchmarking studies on nanopore data are lacking. We systematically evaluated performance of bacterial taxonomic classification for metagenomics nanopore sequencing data for several commonly used classifiers, using standardized reference sequence databases, on the largest collection of publicly available data for defined mock communities thus far (nine samples), representing different research domains and application scopes. Our results categorize classifiers into three categories: low precision/high recall; medium precision/medium recall, and high precision/medium recall. Most fall into the first group, although precision can be improved without excessively penalizing recall with suitable abundance filtering. No definitive 'best' classifier emerges, and classifier selection depends on application scope and practical requirements. Although few classifiers designed for long reads exist, they generally exhibit better performance. Our comprehensive benchmarking provides concrete recommendations, supported by publicly available code for reassessment and fine-tuning by other scientists.
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