ArticleGenome research2020
LEMMI: a continuous benchmarking platform for metagenomics classifiers.
Article in Genome research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- LEMMIv2: benchmarking framework for metagenomic and 16S amplicon profilers with a catalogue of evaluated tools.Genome biology · 2026Article
- Quest for Orthologs in the era of Data Deluge and AI: Challenges and Innovations in Orthology Prediction and Data Integration.Journal of molecular evolution · 2025Review
- ganon2: up-to-date and scalable metagenomics analysis.NAR genomics and bioinformatics · 2025Article
- Hiding in plain sight: the biomolecular identification of pinniped use in medieval manuscripts.Royal Society open science · 2025Article
- The mOTUs online database provides web-accessible genomic context to taxonomic profiling of microbial communities.Nucleic acids research · 2025Article
- Impact of simulation and reference catalogues on the evaluation of taxonomic profiling pipelines.Microbial genomics · 2025Article
- MNBC: a multithreaded Minimizer-based Naïve Bayes Classifier for improved metagenomic sequence classification.Bioinformatics (Oxford, England) · 2024Article
- Challenges and best practices in omics benchmarking.Nature reviews. Genetics · 2024Review
- Challenges and opportunities in sharing microbiome data and analyses.Nature microbiology · 2023Review
- OrthoDB v11: annotation of orthologs in the widest sampling of organismal diversity.Nucleic acids research · 2023Article
- Metagenome analysis using the Kraken software suite.Nature protocols · 2022Review
- Crowdsourced benchmarking of taxonomic metagenome profilers: lessons learned from the sbv IMPROVER Microbiomics challenge.BMC genomics · 2022Article
- The standardisation of the approach to metagenomic human gut analysis: from sample collection to microbiome profiling.Scientific reports · 2022Article
- Aberration-corrected ultrafine analysis of miRNA reads at single-base resolution: a k-mer lattice approach.Nucleic acids research · 2021Article
- Taxonomic analysis of metagenomic data with kASA.Nucleic acids research · 2021Article
- Evaluation of the Microba Community Profiler for Taxonomic Profiling of Metagenomic Datasets From the Human Gut Microbiome.Frontiers in microbiology · 2021Article
- Measuring the microbiome: Best practices for developing and benchmarking microbiomics methods.Computational and structural biotechnology journal · 2020Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Studies of microbiomes are booming, along with the diversity of computational approaches to make sense out of the sequencing data and the volumes of accumulated microbial genotypes. A swift evaluation of newly published methods and their improvements against established tools is necessary to reduce the time between the methods' release and their adoption in microbiome analyses. The LEMMI platform offers a novel approach for benchmarking software dedicated to metagenome composition assessments based on read classification. It enables the integration of newly published methods in an independent and centralized benchmark designed to be continuously open to new submissions. This allows developers to be proactive regarding comparative evaluations and guarantees that any promising methods can be assessed side by side with established tools quickly after their release. Moreover, LEMMI enforces an effective distribution through software containers to ensure long-term availability of all methods. Here, we detail the LEMMI workflow and discuss the performances of some previously unevaluated tools. We see this platform eventually as a community-driven effort in which method developers can showcase novel approaches and get unbiased benchmarks for publications, and users can make informed choices and obtain standardized and easy-to-use tools.
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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.