Metabolomics experiments based on mass spectrometry (MS) or nuclear magnetic resonance (NMR) produce large and complex data sets. This course will introduce approaches to process and analyse data and design high-quality experiments. Through hands-on workshops and lectures highlighting the different concepts you will get a thorough basis for tackling the challenges in metabolomics data analysis.
This course targets professionals working in health and life sciences (e.g., food industry, breeding and seed business, pharmaceutical companies, hospital laboratories, biotech and agro chemical industry). Presumed knowledge: a background in and basic understanding of analytical chemistry or metabolomics by work or education. No prior knowledge of programming, mathematics or statistics is assumed.
The course provides an overview of the tools and approaches used to design a study, process and analyse the data, avoiding common traps and mistakes. Principles will be explained in a general way, meaning they are valid for all common data acquisition platforms (e.g., NMR and MS) and software packages. The focus is on understanding, correct application and interpretation. After the course, participants are able to design appropriate experiments for typical metabolomics studies, taking into account quality assurance and quality control considerations.
The course is set up in blocks covering all topics relevant for experimental design and preprocessing, exploratory analysis and modelling. The material is presented in an attractive mix of lectures and hands-on computer practicals using real-world data. This set-up offers participants an ideal mix to learn how to:
- choose pretreatment strategies relevant for the goal of the analysis and the data characteristics;
- select and execute appropriate data analysis methods to link metabolite data to properties of interest;
- interpret and assess the results of these data analysis methods.
This interactive course is led by experts in the field of metabolomics. They offer interactive tuition with Q&A sessions and the opportunity to discuss case studies submitted by the participants.