What is W4M ?
Workflow4Metabolomics (W4M) is a core resource providing online data processing and analysis to the metabolomics community. W4M started as a collaborative project, especially funding by regional grants and national French grants. The French Institute of Bioinformatics (IFB - ELIXIR-FR) and the French Infrastructure for Metabolomics and Fluxomics (MetaboHUB) have therefore joined their complementary expertise to develop and maintain the Workflow4Metabolomics infrastructure (W4M) bioinformatics resource for online metabolomics data analysis (http://workflow4metabolomics.org ; Giacomoni & Le Corguillé et al., 2015).
W4M resource is based on the Galaxy environment that provides user-friendly interfaces to build, run, and share comprehensive data analysis workflows (Guitton et al., 2017) and gives access to a High Performance Computing environment the ELIXIR-FR/IFB infrastructure. Thus, W4M offers more than 40 tools to process data from all three main technologies (NMR, GCMS, LCMS), including unique algorithms developed by the W4M developers themselves. Data and workflows can be re-used and publicly shared, thus becoming useful references for the community. Finally, the platform provides many tutorials and a help desk.
W4M R&D effort aims to implement new galaxy data visualization tools and improving the interoperability of existing resources (MetExplore, MetaboLights, MassBank), by providing these services through Galaxy and by making new connections from Galaxy to other services.
W4M e-infrastructure is also the first repository for data analysis workflows dedicated to metabolomics, allowing case study histories sharing through the W4M public web portal and associated with a digital object identifier (DOI) which can be cited in publications (https://workflow4metabolomics.org/referenced_W4M_histories).
W4M was the first first worldwide implementation of a metabolomics data analysis workflow system. Since 2016, W4M supported several initiatives (MetaboFlow consortium, ChemFlow, ...) relevant for both sustainability and development of tools for a larger community scope. After being involved in the PhenoMeNal H2020 project (e-infrastructure for the analysis of large scale human phenotyping data) led by the European Bioinformatics Institute (EBI), today, W4M plays a key role in new ELIXIR “Metabolomics” and “Galaxy” communities and is involved in the ELIXIR Implementation Study on Metabolite Identification led by ELIXIR-NL.
W4M has more than 1500 users worldwide and provides R&D services to small teams as well as big consortia, such as MetaboHUB and the ANR-RHU CHOPIN project (CHOlesterol Personalized INnovation). W4M is being currently supported by IFB and MetaboHUB to become a core service (Service Delivery Plan) from ELIXIR-FR. Since 2014, W4M proposes regular trainings as workshops and summer schools (RFMF, H2020 PhenoMeNal, Metabolomics society…) and its Workflow4Experimenters (W4E) annual international course. Combining lectures from experts and w4m-based practical sessions, Workflow4metabolomics is participating to the usemetabo.org opencourse and, proposing two initiative sessions including LC/MS and NMR untargeted metabolomics data analysis.
Why choosing NMR or LC/MS ?
In a large panel of fields as nutrition, health, agriculture and biotechnology, there is a growing need to perform large-scale identification and quantification of metabolites. Cutting-edge analytical approaches as NMR, ultra-high resolution mass spectrometry and
liquid/gas chromatography coupled to mass spectrometry allow the characterization of compounds in biological matrices. In particular, untargeted analysis is a first-class approach for knowledge/biomarker discovery.
Mass spectrometry (MS) and Nuclear Magnetic Resonance (NMR) are the two most widely used analytical tools in metabolomics. Either analytical platform has its own characteristic advantages and contraints but neither method is capable of detecting all
metabolites present in complex matrices. NMR has the advantage of being a non-destructive technique, with high analytical reproducibility and simplicity of sample preparation. Although improvements in the sensitivity of NMR have been achieved with cryoprobes
and higher magnetic fields, the sentivity is still limited because it allows only the detection of moderately to highly abundant metabolites and therefore requires a larger volume of sample. Hyphenated mass spectrometry methods such as GC/MS and LC/MS offer
higher sensitivity and selectivity, but it needs complicated sample extraction procedures, is affected by ionization suppression and matrix effect, and has relatively longer analysis time. MS and NMR platforms have different extraction, data acquisition and
processing methods because of different physical and chemical properties. Processing methods for these platforms are described in this course. Combining multiple metabolomics platforms is a way to expand metabolite coverage.
You already produced your metabolomic data with your favorite instrument and you want to process them on a unique analysis pipeline? Learning bases about untargeted metabolomics data analysis? Furthermore, you want to increase your knowledge on generic data analysis tools and pipelines in LC/MS or in NMR, including preprocessing, normalization, quality control, statistical analysis (Univariate, Multivariate PLS/OPLS) and annotation key steps? The W4M part of the usematebo.org Open Course will show you how to use the Galaxy plateform, organize your analysis project, familiarize yourself with concepts and practices introduced by experts in chemistry, biostatistics, bioinformatics and data scientists. So bring your data and let’s go analyzing them on W4M!!
This course aims at introducing chemists, biologists or statisticians to all the necessary knowledge for metabolomic studies, regarding NMR or MS spectra analysis.
Skills in NMR spectroscopy or Mass Spectrometry are needed to understand preprocessing and annotation steps. Basic statistical analysis knowledge can be useful although not mandatory. Some capacity to manage or use basic data formats are required.
In order to access to the W4M Galaxy instance, you need to request an account: https://workflow4metabolomics.org/account
How does it work ?
For both NMR and MS techniques, this course is organized as follows: first course section adresses uploading (raw) files. Then pre-processing and processing steps are presented. Statistical analyses are included in the fourth step, and the final course section tackles the annotation of compounds.
W4M using Nuclear Magnetic Resonance
W4M using Liquid Chromatography – Mass Spectrometry