This course develops a metabolomics investigation from experimental design through data preparation and statistical interpretation. Lectures, practical work and group discussion connect analytical chemistry and data collection with reproducible analysis. Exercises cover R data handling and visualisation, xcms processing of untargeted mass-spectrometry data, quality control, missing values and compound annotation. The final module compares univariate tests, multiple-testing correction, principal-component methods, partial least squares and random forests for metabolomic matrices. Sessions: 16,
In Biostatistics and Metabolomics