Metabolomics with R/Bioconductor

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, 17, 18 and 20 November, 09:30–13:30, Europe/Berlin (CET, UTC+01:00); no session on 19 November.

Live online training; fee €480. Familiarity with R is assumed; prior metabolomics experience is useful.