Create, run, share, publish, and reference your LC–MS, FIA–MS, GC–MS, and NMR data analysis workflows with the Workflow4Metabolomics 3.0 Galaxy online infrastructure for metabolomics

Abstract

Metabolomics is a key approach in modern functional genomics and systems biology.Due to the complexity of metabolomics data, the variety of experimental designs, and the variety of existing bioinformatics tools, providing experimenters with a simple and efficient resource to conduct comprehensive and rigorous analysis of their data is of utmost importance. In 2014, we launched the Workflow4Metabolomics (W4M; http://workflow4metabolomics.org) online infrastructure for metabolomics built on the Galaxy environment, which offers user-friendly features to build and run data analysis workflows including preprocessing, statistical analysis, and annotation steps. Here we present the new W4M 3.0 release, which contains twice as many tools as the first version, and provides two features which are, to our knowledge, unique among online resources. First, data from the four major metabolomics technologies (i.e., LC-MS, FIA-MS, GC-MS, and NMR) can be analyzed on a single platform. By using three studies in human physiology, alga evolution, and animal toxicology, we demonstrate how the 40 available tools can be easily combined to address biological issues.Second, the full analysis (including the workflow, the parameter values, the input data and output results) can be referenced with a permanent digital object identifier (DOI).Publication of data analyses is of major importance for robust and reproducible science. Furthermore, the publicly shared workflows are of high-value for e-learning and training. The Workflow4Metabolomics 3.0 e-infrastructure thus not only offers a unique online environment for analysis of data from the main metabolomics technologies, but it is also the first reference repository for metabolomics workflows.

Nutrimetabolomics: An Integrative Action for Metabolomic Analyses in Human Nutritional Studies

“…An interesting alternative is represented by web‐based workflow management solutions. In the field of metabolomics, Workflow4Metabolomics (W4M; http://workflow4metabolomics.org) permits the building and running of complete data analysis pipelines, which can be stored and documented together with the associated data, published on W4M (i.e., shared with the community) and referenced with a digital object identifier (DOI), which can be cited in publications . Another example is PhenoMeNal (http://phenomenal-h2020.eu/home/), a comprehensive and standardized e‐infrastructure that supports the data processing and analysis pipelines for molecular phenotype data generated by metabolomics applications.…”

Development of a Headspace Solid‐Phase Microextraction Gas Chromatography‐Mass Spectrometry Method to Study Volatile Organic Compounds (VOCs) Emitted by Lavender Roots

“…To obtain the final matrix with samples in row and retention times in columns, raw data were aligned using metaMS.runGC function of Workflow 4 Metabolomics (W4 M) (retention time tolerance of 0.05 min; minimum features of 5; and a threshold value of 0.7). [41,42] All other statistical analyses were done using R v3.5.1 software (R Foundation, Institute for Statistics and Mathematics, Austria). Three technical replicates were performed for each plant and the repeatability was estimated by the standard deviation (SD) and variation coefficient (CV) among replicates.…”

The future of metabolomics in ELIXIR

“…Workflow management e-infrastructures such as Workflow4Metabolomics ( http://workflow4metabolomics.org/) 34, 35 , PhenoMeNal, and Galaxy-M 36 are key European resources built on the Galaxy environment 37 that simultaneously address the two challenges of 1) high-performance, user-friendly, modular, and reproducible data analysis (needed by the experimental community), and 2) collaborative contributions from the bioinformatics community. Comprehensive workflows for preprocessing, statistical analysis, and annotation of data from liquid chromatography - MS (LC-MS), direct infusion MS (DIMS), gas chromatography - MS (GC-MS), and NMR technologies can be created, tailored, run, saved, shared, and publicly referenced with digital object identifiers ( http://workflow4metabolomics.org/referenced_W4M_histories).…”