Course syllabus
National course open for PhD students, postdocs, researchers and other employees in all Swedish universities, in need of metabolomics data analysis skills. We also welcome applications from outside of Sweden and from the non-academic sector.
Next course
March 23rd - 25th, 2026
KBC-Glasburen, KBC-huset, Linnaeus väg 6, 907 36 Umeå, Sweden Mazemap
Application
Please apply using this form.
Application closes: 2026-02-16
Confirmation to accepted participants: 2026-02-20
Covered topics
- Designing a metabolomics experiment
- Principles of LCMS, GCMS and NMR techniques
- Pre-processing (peak picking, alignment, annotation) of raw metabolomics and exposomics data with MS-Dial
- Quality controls of raw data
- Analysis of metabolomics and exposomics data using PCA, (O)PLS and (O)PLS-DA in R and SIMCA
software - Assessment of model performance and selection of differential metabolites
Learning outcomes
Upon completion of this course, you will be able to:
1. Describe the key steps and components of a typical metabolomics workflow.
2. Explain the fundamental principles and differences between LC-MS, GC-MS, and NMR
techniques in metabolomics.
3. Pre-process raw metabolomics data using MS-DIAL, including peak picking, alignment,
and annotation.
4. Apply multivariate (e.g., PCA, PLS, PLS-DA) methods to metabolomics datasets using R
and SIMCA software
5. Evaluate the assumptions, strengths, and limitations of multivariate methods used in
metabolomics.
6. Interpret the biological significance of results from multivariate methods.
7. Select appropriate data processing and statistical approaches based on study design and
research objectives.
Entry requirements
The following is a list of skills required for being able to follow the course and complete the
exercises:
● Ability to bring your own laptop with R and SIMCA installed for practical exercises
● Programming experience in R is desirable
Selection criteria
Due to limited space the course can accommodate a maximum of 20 participants. If we receive
more applications, participants will be selected based on selection criteria, including (but not
limited to) correct entry requirements, motivation to attend the course, as well as gender and
geographical balance.
Fees
2000 SEK for academic participants
9500 SEK for non-academic participants
The fee includes lunches and coffee.
Schedule (will be added soon..)
Course teachers
Elena Dracheva (Umeå University) – Course leader,
Katie Bennett (Umeå University) – Course leader,
Carl Brunius (Chalmers University of Technology) – Course teacher,
Hans Stenlund (Umeå University) – Course teacher,
Stefano Papazian (Stockholm University) – Course teacher,
Ilona Dudka (Umeå University) – Course lecturer
Contact