Course coordinators
Andrew Stubbs, Erasmus MC
Miaomiao Zhou, Avans University of Applied Sciences

Course credits
1.5 ECTS

Course overview
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. Presentations are followed by hands-on computer sessions using Linux command line tools, Galaxy and R to directly apply and get more insight in the analysis methods. One afternoon is dedicated to the analysis of a new data set, allowing the students to refresh and extend their analysis skills. Students can also bring their own RNA-seq data for practicing. We will also explore the potential of long-read based RNA-seq in a Friday afternoon literature club. After the course, the presentations, practicals and test data will remain available for future reference. Software packages used are freeware.

Target audience
Participants for the RNA-seq course should preferably have participated in a general next-generation sequencing (NGS) course or otherwise have some hands-on experience with NGS data analysis. The course is aimed at PhD students and post-docs, but scientific programmers and data analysts with a background in biology and bioinformatics may also attend.

Learning outcomes
After having followed this course:

• The participant has insight into the issues involved in good experimental design of RNA-seq experiments.
• The participant knows and can perform analysis steps in reference-based and de novo RNA-seq data analysis, and visually present and judge the results for:

• quality control and preprocessing,
• finding differentially expressed genes,
• variant calling,
• cluster analysis,
• classification analysis,
• pathway testing.

• 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 is able to critically judge the statistical analysis of RNA-seq data performed by others.

Read more and register now via: https://www.dtls.nl/courses/rna-seq-data-analysis-2022/

BioSB research school