Training

The aim of this course is to familiarise the participants with advanced data analysis methodologies and provide hands-on training on the latest analytical approaches. Lectures will give insight into how biological knowledge can be generated from RNA-seq experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of RNA-seq data under the guidance of the lecturers and teaching assistants.

During this course you will learn about:

• High-throughput sequencing technology
• Quality control of raw reads: FASTQC and fastx toolkit
• Considerations on experiment design for RNA-seq
• Read pseudoalignment and quantification: kallisto, salmon
• Differential expression analysis and differential exon usage: R, edgeR, DESeq2, DEXSeq
• Downstream DE data processing and gene target discovery
• Single cell RNA-seq analysis: scran, scater

After this course you should be able to:

• Understand the advantages and limitations of the high-throughput assays presented
• Assess the quality of your datasets
• Understand the difference between short read aligners
• Perform alignment and quantification of expression of RNA-seq datasets
• Understand the challenges of single cell sequencing analysis

We invite participants to bring along a poster to display for the duration of the course. These will serve to facilitate discussion about your research and to convey your reasons for attending the course to others. Posters must be A2 portrait (420mm x 594mm).