Training material to analyse Metabolomics data in Galaxy - LCMS, FIAMS, GCMS and NMR
Most of the training are using the tools from the Workflow4Metabolomics (W4M) project.
Before diving into this topic, we recommend you to have a look at:
|Lesson||Slides||Hands-on||Input dataset||Workflows||Galaxy tour|
|Introduction to Metabolomics||slides|
|Mass spectrometry imaging: Examining the spatial distribution of analytes||tutorial Toggle Dropdown||zenodo_link||workflow|
|Mass spectrometry imaging: Finding differential analytes||tutorial Toggle Dropdown||zenodo_link||workflow|
You can use a public Galaxy instance which has been tested for the availability of the used tools. They are listed along with the tutorials above.
This material is maintained by:
For any question related to this topic and the content, you can contact them or visit our Gitter channel.
This material was contributed to by:
- Franck Giacomoni, Gildas Le Corguillé, Misharl Monsoor, Marion Landi, Pierre Pericard, Mélanie Pétéra, Christophe Duperier, Marie Tremblay-Franco, Jean-François Martin, Daniel Jacob, Sophie Goulitquer, Etienne A. Thévenot and Christophe Caron: Workflow4Metabolomics: A collaborative research infrastructure for computational metabolomics
- Yann Guitton, Marie Tremblay-Franco, Gildas Le Corguillé, Jean-François Martin, Mélanie Pétéra, Pierrick Roger-Mele, Alexis Delabrière, Sophie Goulitquer, Misharl Monsoor, Christophe Duperier, Cécile Canlet, Rémi Servien, Patrick Tardivel, Christophe Caron, Franck Giacomoni, Etienne A. Thévenot: 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
- Smith, C.A., Want, E.J., O'Maille, G., Abagyan,R., Siuzdak, G: XCMS: Processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching and identification.