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Mass spectrometry: LC-MS preprocessing with XCMS

This workflow is composed with the XCMS tool R package (Smith, C.A. 2006) able to extract, filter, align and fill gapand the possibility to annotate isotopes, adducts and fragments using the CAMERA R package (Kuhl, C 2012). https://training.galaxyproject.org/training-material/topics/metabolomics/tutorials/lcms-preprocessing/tutorial.html

  • Author(s):
  • workflow4metabolomics
  • Release: 1.0
  • License: MIT
  • UniqueID: 4b4dda98-7422-4207-b9bd-62c11ce8e0f0

Mass spectrometry: LC-MS preprocessing with XCMS

This workflow uses the XCMS tool R package (Smith, C.A. 2006) to extract, filter, align and fill gaps, and uses the CAMERA R package (Kuhl, C 2012) to annotate isotopes, adducts and fragments.

🎓 For more information see the Galaxy Training Network tutorial: Mass spectrometry: LC-MS preprocessing with XCMS

Inputs

sampleMetadata

The sampleMetadata tabular file corresponds to a table containing information about your samples

A sample metadata file contains various information for each of your raw files:

  • Classes which will be used during the preprocessing steps
  • Analytical batches which will be useful for a batch correction step, along with sample types (pool/sample) and injection order
  • Different experimental conditions which can be used for statistics
  • Any information about samples that you want to keep, in a column format

The content of your sample metadata file has to be filled by you, since it is not contained in your raw data. Note that you can either:

  • Upload an existing metadata file
  • Use a template to create one (because it can be painful to get the sample list without misspelling or omission)
    • Generate a template with the xcms get a sampleMetadata file tool available in Galaxy
    • Fill it using your favorite table editor (Excel, LibreOffice)
    • Upload it within Galaxy

Formats: tab-separated values as tsv, tab, txt, ...

Mass-spectrometry Dataset Collection

Mass-spectrometry data files gathered in a Galaxy Dataser Collection

Formats: open format as mzXML, mzMl, mzData and netCDF

Main steps

  1. MSnbase readMSData: read the mzXML and prepare for xcms
  2. XCMS findChromPeaks: peak picking
  3. XCMS groupChromPeaks: determining shared ions across samples
  4. XCMS adjustRtime: retention time correction
  5. XCMS fillChromPeaks: integrating areas of missing peaks
  6. CAMERA.annotate: annotation