Content Overview

This online course explores the tools and approaches that are used to process and analyse metabolomics data. You will investigate the challenges that are typically encountered in the analysis of metabolomics data, and provide solutions to overcome these problems.

Topics Covered

• An introduction to metabolomics
• An overview of the untargeted metabolomics workflow
• The influence of experimental design and data acquisition on data analysis and data quality
• An overview of processing NMR data
• Processing direct infusion mass spectrometry data with a hands-on exercise
• Processing liquid chromatography-mass spectrometry data with hands-on exercises
• Reporting standards and data repositories
• Data analysis, detecting outliers and drift, and pre-treatment methods
• Univariate data analysis with a hands-on exercise
• Multivariate data analysis (including unsupervised and supervised approaches) with hands-on exercises
• The importance of statistical validation of results
• Computational approaches for metabolite identification and translation of results into biological knowledge with hands-on exercises
• What are the future challenges for data processing and analysis in metabolomics

Software used during the course

• Galaxy to process direct infusion mass spectrometry data
• XCMS online to process liquid chromatography – mass spectrometry data
• MetaboAnalyst in the univariate and multivariate data analysis exercises
• Metabolite annotation using PUTMEDID_ID operating in the Taverna workflow environment

Level

The course would be ideally suited to MSc / PhD students or scientists who are in the early stages of analysing metabolomics data. No previous knowledge of the data processing and statistical analysis approaches is assumed, but a basic understanding of the metabolome, and the analytical techniques applied in the metabolomics field would be beneficial. A pre-course recommended reading list will be provided.