LC/MS data analysis with XCMS and MetFrag on PhenoMeNal
Metabolite identification is a crucial step when trying to understand e.g. the courses of a disease on the metabolomic level. In this webinar we will briefly introduce the MetFrag system and then focus on using MetFrag in Galaxy as part of the PhenoMeNal infrastructure. The MetFrag workflow goes a first step to annotate molecules from compound (metabolite) databases to MS/MS (tandem mass spectrometry) spectra. This annotation is based on the mapping of in silico generated fragments to the experimental spectra and scoring of these mappings based on different criteria. The workflow consists of different steps that include the pre-processing of the data using the R packages XCMS, MSnbase and CAMERA to read the data from a given mzML file and to detect and annotate features. Given this annotation MetFrag parameter sets are generated that are passed to the MetFrag Batch tool performing the actual processing that includes the annotation of molecular structures to the data.
This webinar was recorded on 23 November 2017. It is best viewed in full screen mode using Google Chrome. The slides from this webinar can be downloaded below.
See the EMBL-EBI training pages for a list of upcoming webinars.
This webinar is for life-scientists who are generating liquid-chromatography mass-spectrometry data who want to learn how workflows within in the PhenoMeNal platform can be used to analyse this data. No prior knowledge of bioinformatics is required but some familiarity with metabolomics experiments is recommended.
For an introduction to the PhenoMeNal portal you can watch our webinar PhenoMeNal: Metabolomics data analysis in the cloud or see our tutorial PhenoMeNal: accessing metabolomics workflows in Galaxy.
No prior knowledge of bioinformatics is required but some familiarity with metabolomics experiments is recommended.