ArticleBMC bioinformatics2019
SLIM: a flexible web application for the reproducible processing of environmental DNA metabarcoding data.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- The Elusive Fraction of Marine Plankton Diversity: Size, Abundance and Taxonomic Composition of 0.2 μm-Filterable Prokaryotes Across Three Contrasting Coastal Environments.Molecular ecology · 2026Article
- Changing sea ice cover led to marine biodiversity shifts in the Late Quaternary.Communications earth & environment · 2026Article
- Expanding the footprint of the Storegga tsunami through new evidence from Arctic marine sediments.Scientific reports · 2025Article
- Sanctuary for vulnerable Arctic species at the Borealis Mud Volcano.Nature communications · 2025Article
- Data on insect biodiversity in a Chinese potato agroecosystem from DNA metabarcoding.Scientific data · 2025Article
- Sediment eDNA metabarcoding reveals the endemism in benthic foraminifera from Arctic methane cold seepages.ISME communications · 2025Article
- Assigning the unassigned: A signature-based classification of rDNA metabarcodes reveals new deep-sea diversity.PloS one · 2024Article
- Metabarcoding reveals high diversity of benthic foraminifera linked to water masses circulation at coastal Svalbard.Geobiology · 2023Article
- VTAM: A robust pipeline for validating metabarcoding data using controls.Computational and structural biotechnology journal · 2023Article
- Vertical organization of microbial communities in Salineta hypersaline wetland, Spain.Frontiers in microbiology · 2023Article
- Shared and contrasting associations in the dynamic nano- and picoplankton communities of two close but contrasting sites from the Bay of Biscay.Environmental microbiology · 2022Article
- APSCALE: advanced pipeline for simple yet comprehensive analyses of DNA metabarcoding data.Bioinformatics (Oxford, England) · 2022Article
- Applying convolutional neural networks to speed up environmental DNA annotation in a highly diverse ecosystem.Scientific reports · 2022Article
- Patterns of eukaryotic diversity from the surface to the deep-ocean sediment.Science advances · 2022Article
- Monitoring the ecological status of rivers with diatom eDNA metabarcoding: A comparison of taxonomic markers and analytical approaches for the inference of a molecular diatom index.Molecular ecology · 2021Article
- DNA Metabarcoding for the Characterization of Terrestrial Microbiota-Pitfalls and Solutions.Microorganisms · 2021Review
- Article
- The Foreign Oligochaete SpeciesBiology · 2020Article
- Planktonic foraminifera eDNA signature deposited on the seafloor remains preserved after burial in marine sediments.Scientific reports · 2020Article
- Environmental DNA and RNA as Records of Human Exposome, Including Biotic/Abiotic Exposures and Its Implications in the Assessment of the Role of Environment in Chronic Diseases.International journal of molecular sciences · 2020Review
Corrections and comments
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5 authors.
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Abstract
backgroundHigh-throughput amplicon sequencing of environmental DNA (eDNA metabarcoding) has become a routine tool for biodiversity survey and ecological studies. By including sample-specific tags in the primers prior PCR amplification, it is possible to multiplex hundreds of samples in a single sequencing run. The analysis of millions of sequences spread into hundreds to thousands of samples prompts for efficient, automated yet flexible analysis pipelines. Various algorithms and software have been developed to perform one or multiple processing steps, such as paired-end reads assembly, chimera filtering, Operational Taxonomic Unit (OTU) clustering and taxonomic assignment. Some of these software are now well established and widely used by scientists as part of their workflow. Wrappers that are capable to process metabarcoding data from raw sequencing data to annotated OTU-to-sample matrix were also developed to facilitate the analysis for non-specialist users. Yet, most of them require basic bioinformatic or command-line knowledge, which can limit the accessibility to such integrative toolkits. Furthermore, for flexibility reasons, these tools have adopted a step-by-step approach, which can prevent an easy automation of the workflow, and hence hamper the analysis reproducibility.
resultsWe introduce SLIM, an open-source web application that simplifies the creation and execution of metabarcoding data processing pipelines through an intuitive Graphic User Interface (GUI). The GUI interact with well-established software and their associated parameters, so that the processing steps are performed seamlessly from the raw sequencing data to an annotated OTU-to-sample matrix. Thanks to a module-centered organization, SLIM can be used for a wide range of metabarcoding cases, and can also be extended by developers for custom needs or for the integration of new software. The pipeline configuration (i.e. the modules chaining and all their parameters) is stored in a file that can be used for reproducing the same analysis.
conclusionThis web application has been designed to be user-friendly for non-specialists yet flexible with advanced settings and extensibility for advanced users and bioinformaticians. The source code along with full documentation is available on the GitHub repository ( https://github.com/yoann-dufresne/SLIM ) and a demonstration server is accessible through the application website ( https://trtcrd.github.io/SLIM/ ).
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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.