Metabolomics data analysis in the Cloud: Live Online Training

Home  /  All  /  Metabolomics data analysis in the Cloud: Live Online Training

Date: Wednesday 6 – Friday 8 June 2018.

The PhenoMeNal consortium is pleased to announce a Live Online Training, via a series of live webinars, in which participants will become familiar with the open-source tools and workflows in the PhenoMeNal infrastructure. This event will include live webinars with time to do supported, self-directed exercises using the resources introduced during the webinars. Each webinar will include a question and answer session and additional sessions will be provided in which to discuss the exercises. You do not need to join all of the webinars, you can dip in and out joining only the webinars that you are interested in. We will be using Slack to keep in touch during the webinars and to provide support.

Syllabus, Tools and Resources

During this course you will learn about:

  • The PhenoMeNal project and available infrastructure
  • Creating a cloud research environment (e.g running in AWS)
  • Tools and workflows in Galaxy

How do I register?

The webinars will be hosted on GotoTraining system, which will require you to download a small plugin to run the webinar. For more details and registration click here (Registration closed)

Agenda: All dates and times are in British Summer Time (GMT+1hr).

6th June


09:30 – 10:15 Getting started with PhenoMeNal

10:15 – 11:00 Introduction to MetaboLights


7th June


9:30- 9:45 Q & A session exercises

09:45 – 10:30 LC/MS data analysis with XCMS and MetFrag

10:30 – 11:15 Data standards For Metabolomics and FAIR datasets: PhenoMeNal Data Management Workflows in Galaxy


8th June


10:15-10:30 Q & A session exercises

10:30 – 11:15 Implementation of highly parallel containerised tools for large-scale metabolomic data analysis in the PhenoMeNal Project

11:15 – 12:00 Statistical workflows with Galaxy

 

 

 


One Comment so far:

  1. […] workshop will provide an introduction to metabolomics data analysis in a cloud computing environment, based […]