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.
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)
- Early bird registration (until February 11, 2024):
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
- The participant has insight into the issues involved in good experimental design of RNA-seq
- 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
- The participant has insight in various RNA-seq platforms, their specificity in solving certain biological questions, and the bottlenecks in these applications.
- The participant has insight into the different algorithms and options available to perform an analysis and can make an informed choice.
- The participant knows the pitfalls of existing analyses and can critically judge the statistical analysis of expression data performed by others.
- 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.