ReviewNature protocols2021
Tutorial: assessing metagenomics software with the CAMI benchmarking toolkit.
Review in Nature protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
32 citing papers in PubMed.
- MetaCAT enables reconstruction of high-quality microbial genomes and their association with host traits from metagenomic data.Nature microbiology · 2026Article
- 2Pipe starts with a question: matching you with the correct pipeline for MAG reconstruction.mSystems · 2026Review
- MetaflowX: a scalable and resource-efficient workflow for multi-strategy metagenomic analysis.Nucleic acids research · 2025Article
- Computational Metagenomics: State of the Art.International journal of molecular sciences · 2025Review
- ganon2: up-to-date and scalable metagenomics analysis.NAR genomics and bioinformatics · 2025Article
- Advancing metagenomic classification with NABAS+: a novel alignment-based approach.NAR genomics and bioinformatics · 2025Article
- CAMI Benchmarking Portal: online evaluation and ranking of metagenomic software.Nucleic acids research · 2025Article
- Non-cyanobacterial diazotrophs support the survival of marine microalgae in nitrogen-depleted environment.Genome biology · 2025Article
- OpenClustered: an R package with a benchmark suite of clustered datasets for methodological evaluation and comparison.BMC medical research methodology · 2025Article
- A blueprint for contemporary studies of microbiomes.Microbiome · 2025Article
- Sequential co-assembly reduces computational resources and errors in metagenome-assembled genomes.Cell reports methods · 2025Article
- Investigating the genomic and metabolic abilities of PGPR Pseudomonas fluorescens in promoting plant growth and fire blight management.Molecular genetics and genomics : MGG · 2024Article
- Seven quick tips for gene-focused computational pangenomic analysis.BioData mining · 2024Article
- Challenges and best practices in omics benchmarking.Nature reviews. Genetics · 2024Review
- Integrating taxonomic signals from MAGs and contigs improves read annotation and taxonomic profiling of metagenomes.Nature communications · 2024Article
- Article
- Effective binning of metagenomic contigs using contrastive multi-view representation learning.Nature communications · 2024Article
- How is Big Data reshaping preclinical aging research?Lab animal · 2023Review
- Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4.Nature biotechnology · 2023Article
- Challenges and opportunities in sharing microbiome data and analyses.Nature microbiology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computational methods are key in microbiome research, and obtaining a quantitative and unbiased performance estimate is important for method developers and applied researchers. For meaningful comparisons between methods, to identify best practices and common use cases, and to reduce overhead in benchmarking, it is necessary to have standardized datasets, procedures and metrics for evaluation. In this tutorial, we describe emerging standards in computational meta-omics benchmarking derived and agreed upon by a larger community of researchers. Specifically, we outline recent efforts by the Critical Assessment of Metagenome Interpretation (CAMI) initiative, which supplies method developers and applied researchers with exhaustive quantitative data about software performance in realistic scenarios and organizes community-driven benchmarking challenges. We explain the most relevant evaluation metrics for assessing metagenome assembly, binning and profiling results, and provide step-by-step instructions on how to generate them. The instructions use simulated mouse gut metagenome data released in preparation for the second round of CAMI challenges and showcase the use of a repository of tool results for CAMI datasets. This tutorial will serve as a reference for the community and facilitate informative and reproducible benchmarking in microbiome research.
Indexed as
Identifiers
33649565What OpenQuestion holds
Registered trials
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.