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Update on technological developments and opportunities with Workflow4Metabolomics

(1) , (1) , (1) , (2) , (3) , (2) , (4, 5) , (5, 4) , (5, 4) , (6) , (7) , (7) , (8) , (1)
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Nils Paulhe
Marie A Tremblay-Franco
Cécile Canlet
Jean-François Martin
  • Function : Author
  • PersonId : 1140388
Cédric Delporte
  • Function : Author
  • PersonId : 1094437
Florence Souard
  • Function : Author
  • PersonId : 1094438
Céline Dalle
  • Function : Author
  • PersonId : 1065602

Abstract

Introduction Metabolomics data analysis is a complex and multistep process, which is constantly evolving with the development of new analytical technologies, mathematical methods, bioinformatics tools and databases. The Workflow4Metabolomics (W4M) infrastructure[1] provides tools in a single online web interface (through Galaxy[1]). During the last two years, W4M has evolved with new upgrades for LC-MS, LC-MSMS, GC-MS and NMR pipelines, including preprocessing, quality control, statistical analysis and annotation tools. W4M also proposes new community resources promoting open science in metabolomics. Technological and methodological innovation W4M major updates include: Specific Galaxy interactive tools with NMRPro[2] for NMR spectra visualization and Xseeker for visualization and annotation of LC-MSMS data (In collaboration with CHOPIN ANR project[3]); An improved MSMS pipeline; New annotation tools suite allowing connexion with PeakForest[4], a new spectral data manager infrastructure for laboratories; New functionalities regarding mixed model computation for repeated measure designs, and improvements in annotation of complex mixture bidimensional NMR spectra. New training resources through the Galaxy Training Network (GTN) are also proposed, and Training Infrastructure as a Service (TIass) is available through the new usegalaxy.fr host. Results and impact W4M’s improvements increase raw data input management and LC/GC-MS(MS) workflow efficiency. We highlight how current advances, along with community training as through the yearly international school Workflow4Experimenters, contribute to open data analysis practices worldwide. In addition the W4M organization on Github repository aims to review code, annotate tools and propose a showcase for contributors from the metabolomics community. References [1] Giacomoni F., Le Corguillé et al (2015). Workflow4Metabolomics: A collaborative research infrastructure for computational metabolomics. Bioinformatics 2015, May 1;31(9):1493-5. doi: 10.1093/bioinformatics/btu813 [2] Mohamed A, Nguyen CH, Mamitsuka H. NMRPro: an integrated web component for interactive processing and visualization of NMR spectra. Bioinformatics. 2016 Jul 1;32(13):2067-8. doi: 10.1093/bioinformatics/btw102. Epub 2016 Feb 26. PMID: 27153725. [3] https://anr.fr/ProjetIA-16-RHUS-0007 [4] Paulhe, N., Canlet, C., Damont, A. et al. PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management. Metabolomics 18, 40 (2022). doi: 10.1007/s11306-022-01899-3 [5] Afgan E. et al. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. Nucleic Acids Res. 2016 Jul 8;44(W1):W3-W10. doi: 10.1093/nar/gkw343
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Dates and versions

hal-03776462 , version 1 (13-09-2022)

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  • HAL Id : hal-03776462 , version 1

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Lain Pavot, Mélanie Pétéra, Nils Paulhe, Yann Guitton, Gildas Le Corguillé, et al.. Update on technological developments and opportunities with Workflow4Metabolomics. Analytics 2022, Sep 2022, Nantes, France. . ⟨hal-03776462⟩
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