Venue:Murray Learning Centre, University of Birmingham
PhenoMeNal (Phenome and Metabolome aNalysis) is a comprehensive and standardised e-infrastructure that supports large scale cloud based data processing and analysis for metabolomics data. The workshop will feature introductory lectures followed by practical sessions where you will be using the PhenoMeNal Gateway (https://portal.phenomenal-h2020.eu/home) to run data-processing and analysis workflows.
Questions?For more information about the workshop please contact James Bradbury: firstname.lastname@example.org
During this session we will have a short introduction to PhenoMeNal as a scientific e-infrastructure that allows researchers to use Cloud computing to tackle Metabolomics data analysis. This will be followed by a demo of the PhenoMeNal Portal, which is the first point of contact for external users to the PhenoMeNal infrastructure, and allow users to both try existing cloud installations and also create their own installations on public cloud providers.
Workflows / Galaxy Intro / Tool Libraries: Pablo Moreno
In this session we will showcase the mechanistic operation of Galaxy, starting with the execution of separate tools manually. Then these same tools will be concatenated in a workflow and the operation of the complete workflow will be shown. Finally, a complete version of the workflow will be shown, from a shared repository of workflows. So we go through the mechanistic usage of Galaxy, from data upload to workflow usage. We will discuss the advantages of using workflows.
MS Workflows: James Bradbury
During this session, the tools and workflows available with PhenoMeNal for MS data processing will be introduced, along with the Galaxy workflow environment. Participants will then use Galaxy tools for processing and annotation of LC-MS data using XCMS and MetFrag. This will be followed by learning how to extract and create Galaxy workflows.
NMR workflows: Daniel Schober & Reza Salek
We will briefly outline two NMR workflows that together cover the basic requirements for NMR Metabolomics data analysis. The first WF covers raw data download from MetaboLights, conversion into the nmrML data standard, preprocessing/FT of the FIDs via the rNMR tool and plotting of NMR spectra. The second WF will exemplify metabolite quantification and identification using the BATMAN tool. In the hands-on part the participants will launch and run the preprocessing WF on the phenoMeNal portal.
Statistics Workflow: Etienne Thévenot
In this section, participants will learn how to perform exploratory data analysis (with Principal Component Analysis), univariate hypothesis testing (including correction for multiple testing), multivariate modeling (with the Partial Least Squares methodology), and feature selection.