Metabolomics and Analytics Centre

Data Analytics and Management

Our group is part of the Metabolomics and Analytics Centre where we accompany the data from its acquisition all the way to the publication of identified associations and biomarkers for a range of human diseases. The generated data of the metabolic measurements are assessed using an in-house quality control tool, and then stored and managed using FAIR principles. It is analyzed using statistical techniques to identify biomarkers or metabolic signatures for a wide range of diseases such as neurodegenerative diseases, e.g., Parkinson’s Disease or Alzheimer’s, or inflammatory conditions such as COVID-19. Further research areas of interest are premature infants and their stressors and predictors for neonatal lung disease. Are you interested in working with us? Please reach out!

Quality control

An in-house quality control tool is used to assess the technical variation in our data using different quality metrices. Generated data is released after a rigorous and detail-oriented investigation by technicians and the statistical expert. After, the data is either used for data analysis by our PhD students or is released to the collaborator.

Data analysis

The statistical analysis is performed after the appropriate steps for the transformation and normalization of the data has been undertaken. Uni- or multi-variate models are applied to identify associations of the metabolome to the phenotype under investigation. This is performed in close collaboration with the clinical collaborators to guide the choice of confounders and interpretation of the results.

Data management

The generated data is stored using the FAIR principles so that they are readily findable, accessible, interoperable, and reusable. For this, we employ public databases such as MetaboLights to publish the acquired metabolomic data.