About
UGent course (Clement) on the statistics of proteomics and RNA-seq data. A map of the course, with my notes organised by topic.
Statistical Genomics (UGent, MSc Bioinformatics / MSc Statistical Data Analysis, 2026 edition). Preprocessing, quantification and differential analysis of high-throughput omics data, with shotgun proteomics and bulk / single-cell RNA-seq as the running examples, plus experimental design. Tooling is R / Bioconductor.
The official material is not copied here: this page links to it. The notes in this section are my own, written topic by topic rather than lecture by lecture.
- Course site: statomics.github.io/SGA
- Source repository: statOmics/SGA
- Material © Lieven Clement, Ghent University, CC BY-SA 4.0.
Course map
Links go to the official slides and tutorials; the last column goes to my notes where they exist.
| Part | Official material | My notes |
|---|---|---|
| Introduction | Position of the course | |
| Introduction | Recap of the linear model, KPNA2 tutorial | linear-models |
| Proteomics | MS basics (PDF), identification (PDF) | |
| Proteomics | Data processing: concepts, tutorial, wrap-up | |
| Proteomics | Inference and design: inference, tutorial, blocking wrap-up |
The published schedule currently covers the introduction and the proteomics module only. RNA-seq (GLMs, overdispersion) and single-cell rows get added as the course progresses.