Various spectrometric methods can be used to conduct metabolomics studies. Nuclear magnetic resonance (NMR) or mass spectrometry (MS) coupled with separation methods, such as liquid or gas chromatography (LC and GC, respectively), are the most commonly used techniques. Once the raw data have been obtained, the real challenge lies in the bioinformatics required to conduct: (i) data processing (including preprocessing, normalization, and quality control); (ii) statistical analysis for comparative studies (such as univariate and multivariate analyses, including PCA or PLS-DA/OPLS-DA); (iii) annotation of the metabolites of interest; and (iv) interpretation of the relationships between key metabolites and the relevant phenotypes or scientific questions to be addressed. Here, we will introduce and detail a stepwise protocol for use of the Workflow4Metabolomics platform (W4M), which provides user-friendly access to workflows for processing of LC-MS, GC-MS, and NMR data. Those modular and extensible workflows are composed of existing standalone components (e.g., XCMS and CAMERA packages) as well as a suite of complementary W4M-implemented modules. This tool suite is accessible worldwide through a web interface and is hosted on UseGalaxy France. The extensible Virtual Research Environment (VRE) provided offers pre-configured workflows for metabolomics communities (platforms, end users, etc.), as well as possibilities for sharing among users. By providing a consistent ecosystem of tools and workflows through Galaxy, W4M makes it possible to process MS and NMR data from hundreds of samples using an ordinary personal computer, after step-by-step workflow optimization. © 2025 Wiley Periodicals LLC. Basic Protocol 1: W4M account creation, working history preparation, and data upload Support Protocol 1: How to prepare an NMR zip file Support Protocol 2: How to convert MS data from proprietary format to open format Support Protocol 3: How to get help with W4M (IFB forum) and how to report a problem on the GitHub repository Basic Protocol 2: LC-MS data processing Alternate Protocol 1: GC-MS data processing Alternate Protocol 2: NMR data processing Basic Protocol 3: Statistical analysis Basic Protocol 4: Annotation of metabolites from LC-MS data Alternate Protocol 3: Annotation of metabolites from NMR data.

Centre Bretagne Normandie INRAE UMR 1349 IGEPP Domaine de la Motte Le Rheu France

Département Médicaments et Technologies pour la Santé Université Paris Saclay CEA INRAE MetaboHUB Gif sur Yvette France

French Armed Forces Biomedical Research Institute Analytical Development and Bioanalysis Unit Brétigny sur Orge France

IFB Institut Français de Bioinformatique CNRS UMS 3601 Génoscope Évry France

Metatoul AXIOM platform National Infrastructure for Metabolomics and Fluxomics MetaboHUB Toxalim INRAE UMR 1331 Toulouse France

Oniris INRAE LABERCA Nantes France

Pharmacognosy Bioanalysis and Drug Development and Analytical Platform Brussels Belgium

Pharmacotherapy and Pharmaceutics Faculty of Pharmacy Université libre de Bruxelles Brussels Belgium

RECETOX Faculty of Science Masaryk University Brno Czech Republic

School of Biosciences University of Birmingham Birmingham United Kingdom

Sorbonne Université CNRS FR2424 ABiMS Station Biologique Roscoff France

These authors contributed equally to this work

Toxalim Research Center in Food Toxicology Toulouse University INRAE UMR 1331 ENVT INP Purpan Paul Sabatier University Toulouse France

Université Clermont Auvergne INRAE UNH Plateforme d'Exploration du Métabolisme MetaboHUB Clermont Clermont Ferrand France

Université Rouen Normandie INSA Rouen Normandie CNRS PBS UMR 6270 Rouen France

Université Rouen Normandie INSERM US 51 CNRS UAR 2026 HeRacLeS PISSARO Rouen France

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