Analysis of bulk RNA-seq data using Chipster

This hands-on course in Zoom introduces the participants to RNA-seq data analysis methods, tools and file formats. It covers the whole workflow from quality control and alignment to quantification and differential expression analysis. The course consists of lectures and exercises. The lectures will be pre-recorded, and participants are requested to view the videos prior to the course and test their knowledge with a set of questions. This gives you more time to reflect on the concepts so that you can use the course time more efficiently for discussions and exercises.

Prerequisites
In the exercises we use analysis tools embedded in the free and user-friendly Chipster software, so no previous knowledge of Unix or R is required, and the course is thus suitable for everybody who is planning to use RNA-seq.

Schedule

1.4.2025 at 9-12:30: Quality control, trimming and alignment

– check the quality of reads with MultiQC
– remove bad quality data with Trimmomatic
– infer strandedness with RseQC
– align RNA-seq reads to the reference genome with HISAT2 and STAR
– efficient analysis: how to assign paired FASTQ files to samples and align all the samples with one click
– perform alignment level quality control using RseQC

2.4.2025 at 9-12:30: Quantifying expression, experiment level QC, differential expression analysis

– quantify expression by counting reads per genes using HTSeq
– check the experiment level quality with PCA plots and heatmaps
– analyze differential expression with DESeq2 and edgeR
– take multiple factors (including batch effects) into account in differential expression analysis
– produce heatmaps of differentially expressed genes
– how to share analysis with a colleague

Trainer

Dr Eija Korpelainen (CSC)