ArticleNAR genomics and bioinformatics2022
RiboTaxa: combined approaches for rRNA genes taxonomic resolution down to the species level from metagenomics data revealing novelties.
Article in NAR genomics and bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Metagenomic analysis of the biofilm community at the oxic-anoxic interface of a deep-underground saline spring at the Baksan Neutrino Observatory.Microbiology spectrum · 2026Article
- Dataset of 111 metagenome-assembled genomes from cattle manure, soil and manured soil samples.Data in brief · 2025Article
- Gene horizontal transfers and functional diversity negatively correlated with bacterial taxonomic diversity along a nitrogen gradient.NPJ biofilms and microbiomes · 2024Article
- Deep underground metagenome-assembled genomes from hydrothermal spring.Microbiology resource announcements · 2024Article
- DeepMPTB: a vaginal microbiome-based deep neural network as artificial intelligence strategy for efficient preterm birth prediction.Biomarker research · 2024Article
- Protist predation promotes antimicrobial resistance spread through antagonistic microbiome interactions.The ISME journal · 2024Article
- Mock community experiments can inform on the reliability of eDNA metabarcoding data: a case study on marine phytoplankton.Scientific reports · 2023Article
- Temporal Changes in the Skin Microbiome of Epidermolysis Bullosa Patients following the Application of Wound Dressings.Journal of clinical medicine · 2023Article
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Authors and funding
3 authors.
Funding
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Abstract
Metagenomic classifiers are widely used for the taxonomic profiling of metagenomics data and estimation of taxa relative abundance. Small subunit rRNA genes are a gold standard for phylogenetic resolution of microbiota, although the power of this marker comes down to its use as full-length. We aimed at identifying the tools that can efficiently lead to taxonomic resolution down to the species level. To reach this goal, we benchmarked the performance and accuracy of rRNA-specialized versus general-purpose read mappers, reference-targeted assemblers and taxonomic classifiers. We then compiled the best tools (BBTools, FastQC, SortMeRNA, MetaRib, EMIRGE, VSEARCH, BBMap and QIIME 2's Sklearn classifier) to build a pipeline called RiboTaxa. Using metagenomics datasets, RiboTaxa gave the best results compared to other tools (i.e. Kraken2, Centrifuge, METAXA2, phyloFlash, SPINGO, BLCA, MEGAN) with precise taxonomic identification and relative abundance description without false positive detection (
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