RNA-seq data analysis

The 9th edition of the RNA-seq Data Analysis course will be held on 8-12 April – 2024 in Breda, The Netherlands. This course covers the basic concepts and methods required for RNA-seq analysis. Particular attention is given to the data analysis pipelines for differential transcript expression and variant calling. The course consists of a mixture of lectures and Galaxy, Linux and R practicals. Also the potential of long-read based RNA-seq and AI based analysis enrichments will be explored.


Avans, room HX175, Hogeschoollaan 1, 4818 CR, Breda

Course coordinators

  • Dr. Andrew Stubbs, Department of Pathology and Clinical Bioinformatics, Erasmus MC
  • Dr. Miaomiao Zhou, Centre of Expertise Material and Energy Transition, Avans University of Applied Sciences

Speakers and moderators

  • Martina Summer-Kutmon, Maastricht Centre for Systems Biology (MaCSBio), Maastricht University
  • Harmen van den Werken, Department of Immunology, Erasmus MC
  • Youri Hoogstrate, Department of Neurology, Erasmus MC
  • Victoria Aguilar Pontes, Fungal biology, Universidad de Córdoba, Spain
  • Leon Mei, Sequencing Analysis Support Core, Department of Biomedical Data Sciences, Leiden University MC.
  • Nikolaos Strepis,  Medical Microbiology & Infectious Diseases, Erasmus MC
  • Radek Szklarczyk and Kasper Derks, Maastricht University MC
  • Wynand Alkema, Hanze University of Applied Sciences
  • Yunlei Li, Jasper Ouwerkerk, Willem de Koning, Myrthe van Baardwijk, Andrew Stubbs Department of Pathology and Clinical Bioinformatics, Erasmus MC
  • Miaomiao Zhou, Bazante Sanders, Sander Boden, Avans University of Applied Sciences

Target audience

This course is intended for those at MSc/PhD level. Working knowledge of NGS is required (If in doubt, please contact the BioSB community manager)

Full participation and performing all practical exercises in this course are awarded with 1,5 ECTS.

Daily program

  • Day 1 08/04: RNA-seq Platforms, Design and Preprocessing,
  • Day 2 09/04: Application of RNA-seq in the clinical world,
  • Day 3 10/04: Variant analysis with RNA-seq data,
  • Day 4 11/04: Clustering, dimension reduction and pathway analysis,
  • Day 5 12/04: Analyze, read, and write smartly: generative AI and RNA-seq analysis enrichment.

Learning objectives

  1. The participant has insight into the issues involved in good experimental design of RNA-seq
  2. The participant knows and can perform analysis steps in reference based and de novo RNA-seq data analysis, visually present and judge the results for:
    • quality control and preprocessing,
    • finding differentially expressed genes,
    • variant calling,
    • cluster analysis,
    • classification analysis,
    • pathway analysis,
    • enriched analysis and visualization
  1. The participant has insight in various RNA-seq platforms, their specificity in solving certain biological questions, and the bottlenecks in these applications.
  2. The participant has insight into the different algorithms and options available to perform an analysis and can make an informed choice.
  3. The participant knows the pitfalls of existing analyses and can critically judge the statistical analysis of expression data performed by others.
  4. The participant gets a preliminary idea how (generative) AI can be used to enrich RNA-seq data analysis and to aid in academic reading/academically.


Fees for this 5-day course are:

  • € 480 (excl. VAT) for PhD/MSc students
  • € 720 (excl. VAT) for academic researchers (non-profit)
  • € 1080 (excl. VAT) for industry participants (for profit)

The course fee includes course materials and catering (coffee, tea and lunch)

You can register for the course by filling out this registration form

Find general enrollment information here.