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Course at Breda, The Netherlands: 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.

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General information

This course is intended for those at MSc/PhD level. Working knowledge of NGS is required.

  • Time: 8-12 April 2024
  • Location: Breda, The Netherlands
  • Fees for this 5-day course are:
    • Early bird registration (until February 11, 2024):
      • € 400 (excl. VAT) for PhD/MSc student
      • *€ 600 (excl. VAT) for academic researchers (non-profit)
      • *€ 900 (excl. VAT) for industry participants (for profit)
    • From February 12, 2024 onwards:
      • € 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)

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,
    • cla* ssification analysis,
    • pathway analysis,
    • enriched analysis and visualization
  3. The participant has insight in various RNA-seq platforms, their specificity in solving certain biological questions, and the bottlenecks in these applications.
  4. The participant has insight into the different algorithms and options available to perform an analysis and can make an informed choice.
  5. The participant knows the pitfalls of existing analyses and can critically judge the statistical analysis of expression data performed by others.
  6. 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.

Registration form

More Info and Registration