ArticleNature communications2023
Removal of false positives in metagenomics-based taxonomy profiling via targeting Type IIB restriction sites.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Perseus: lineage-aware refinement of Kraken2 taxonomic classification for long read metagenomes.Bioinformatics (Oxford, England) · 2026Article
- Temporal Alignment of Wastewater Signals with Clinical Indicators of Respiratory Illness Postpandemic, Texas, USA.Emerging infectious diseases · 2026Article
- Comprehensive taxonomic identification of microbial species in metagenomic data using SingleM and Sandpiper.Nature biotechnology · 2026Article
- Sphingomonas paucimobilis-Driven Epithelial-Endothelial Transition in Adenomyosis Pathogenesis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Filtering for truth: high-precision taxonomic classification in nanopore shotgun metagenomics data through a KMA-based bioinformatic pipeline (KAPTAIN).BMC genomics · 2026Article
- Supragingival Plaque Microbial Signatures Between Radiation Related Caries and Common Caries.International dental journal · 2025Article
- Detection ofFood chemistry. Molecular sciences · 2025Article
- Enriched Long-Read Sequencing of Co-circulating Viruses in Complex Samples.Molecular biology and evolution · 2025Article
- Challenges and Opportunities in Analyzing Cancer-Associated Microbiomes.Cancer research · 2025Review
- Rapid species-level metagenome profiling and containment estimation with sylph.Nature biotechnology · 2025Article
- 2bRAD-M reveals circulating microbiome in chronic antibody-mediated rejection (CAMR) and IgA nephropathy (IgAN) after kidney transplantation.BMC microbiology · 2025Article
- 2bRAD-M Reveals the Characteristics of Urinary Microbiota in Overweight Patients with Urinary Tract Stones.Biomedicines · 2025Article
- Urobiome of patients with diabetic kidney disease in different stages is revealed by 2bRAD-M.Journal of translational medicine · 2025Article
- Circulating microbiome DNA features and its effect on predicting clinicopathological characteristics of patients with colorectal cancer.Journal of translational medicine · 2025Article
- Exploring extreme environments in Türkiye for novel P450s through metagenomic analysis.PloS one · 2025Article
- 2bRAD-M reveals differences in microbial communities between Modic changes and disc herniation.Frontiers in cellular and infection microbiology · 2025Article
- Comparison between metatranscriptomics and viral metagenomics, 16S, and host transcriptomics for comprehensive profiling of the respiratory microbiome and host response.Frontiers in microbiology · 2025Article
- RFW captures species-level metagenomic functions by integrating genome annotation information.Cell reports methods · 2024Article
- Article
- MetaAll: integrative bioinformatics workflow for analysing clinical metagenomic data.Briefings in bioinformatics · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Accurate species identification and abundance estimation are critical for the interpretation of whole metagenome sequencing (WMS) data. Yet, existing metagenomic profilers suffer from false-positive identifications, which can account for more than 90% of total identified species. Here, by leveraging species-specific Type IIB restriction endonuclease digestion sites as reference instead of universal markers or whole microbial genomes, we present a metagenomic profiler, MAP2B (MetAgenomic Profiler based on type IIB restriction sites), to resolve those issues. We first illustrate the pitfalls of using relative abundance as the only feature in determining false positives. We then propose a feature set to distinguish false positives from true positives, and using simulated metagenomes from CAMI2, we establish a false-positive recognition model. By benchmarking the performance in metagenomic profiling using a simulation dataset with varying sequencing depth and species richness, we illustrate the superior performance of MAP2B over existing metagenomic profilers in species identification. We further test the performance of MAP2B using real WMS data from an ATCC mock community, confirming its superior precision against sequencing depth. Finally, by leveraging WMS data from an IBD cohort, we demonstrate the taxonomic features generated by MAP2B can better discriminate IBD and predict metabolomic profiles.
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