ArticleNucleic acids research2020
Taxonomic classification method for metagenomics based on core protein families with Core-Kaiju.
Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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20 citing papers in PubMed, 33 citations in OpenAlex.
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- 16S rRNA sequence captures microbial functional potential.bioRxiv : the preprint server for biology · 2026Article
- Multiple hypervariable markers improve mycobiome classification in metatranscriptome and metagenome data.Communications biology · 2026Article
- Linking complex microbial interactions and dysbiosis through a disordered Lotka-Volterra model.eLife · 2026Article
- Anellovirus abundance as an indicator for viral metagenomic classifier utility in plasma samples.Virology journal · 2025Article
- Neurospora intermedia from a traditional fermented food enables waste-to-food conversion.Nature microbiology · 2024Article
- Emergent ecological patterns and modelling of gut microbiomes in health and in disease.PLoS computational biology · 2024Article
- Methanogenic patterns in the gut microbiome are associated with survival in a population of feral horses.Nature communications · 2024Article
- Construction of high-quality genomes and gene catalogue for culturable microbes of sugarcane (Saccharum spp.).Scientific data · 2024Article
- Application and Comparison of Machine Learning and Database-Based Methods in Taxonomic Classification of High-Throughput Sequencing Data.Genome biology and evolution · 2024Article
- Emergent Functional Organization of Gut Microbiomes in Health and Diseases.Biomolecules · 2023Article
- The Application of Metagenomics to Study Microbial Communities and Develop Desirable Traits in Fermented Foods.Foods (Basel, Switzerland) · 2022Review
- RiboTaxa: combined approaches for rRNA genes taxonomic resolution down to the species level from metagenomics data revealing novelties.NAR genomics and bioinformatics · 2022Article
- Article
- RdRp-based sensitive taxonomic classification of RNA viruses for metagenomic data.Briefings in bioinformatics · 2022Article
- Identification and characterization of a novel metallo β-lactamase, SZM-1, in Shenzhen Bay, South China.Frontiers in microbiology · 2022Article
- Metagenomic-Metabolomic Mining ofFrontiers in microbiology · 2022Article
- Microbial Community Dynamics during Biodegradation of Crude Oil and Its Response to Biostimulation in Svalbard Seawater at Low Temperature.Microorganisms · 2021Article
- Comparative Analysis of 16S rRNA Gene and Metagenome Sequencing in Pediatric Gut Microbiomes.Frontiers in microbiology · 2021Article
- Upscaling Statistical Patterns from Reduced Storage in Social and Life Science Big Datasets.Entropy (Basel, Switzerland) · 2020Article
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Authors and funding
5 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Characterizing species diversity and composition of bacteria hosted by biota is revolutionizing our understanding of the role of symbiotic interactions in ecosystems. Determining microbiomes diversity implies the assignment of individual reads to taxa by comparison to reference databases. Although computational methods aimed at identifying the microbe(s) taxa are available, it is well known that inferences using different methods can vary widely depending on various biases. In this study, we first apply and compare different bioinformatics methods based on 16S ribosomal RNA gene and shotgun sequencing to three mock communities of bacteria, of which the compositions are known. We show that none of these methods can infer both the true number of taxa and their abundances. We thus propose a novel approach, named Core-Kaiju, which combines the power of shotgun metagenomics data with a more focused marker gene classification method similar to 16S, but based on emergent statistics of core protein domain families. We thus test the proposed method on various mock communities and we show that Core-Kaiju reliably predicts both number of taxa and abundances. Finally, we apply our method on human gut samples, showing how Core-Kaiju may give more accurate ecological characterization and a fresh view on real microbiomes.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.