Detecting differentially expressed genes with RNA-seq
Instructor: Dr. Eija Korpelainen
Dr Eija Korpelainen works currently as a Product manager at CSC – IT Center for Science. Being the national supercomputing centre, CSC provides bioinformatics services for all the universities and research institutes in Finland. Eija has long experience in enabling life scientists to analyze high-throughput data. She has run over 100 training courses in Finland and abroad, and her team has established a popular YouTube channel with tutorial videos. The book “RNA-seq data analysis – practical approach” by Korpelainen et al has been one of the most popular bioinformatics books in recent years. In order to enable biologists to analyze data more efficiently, her team has developed the open source analysis software Chipster which is used worldwide. Eija has participated in several international consortia including the EU funded EMBRACE, AllBio and SeqAhead, and she is currently the national training coordinator of the European ELIXIR initiative. Eija has been involved in GOBLET from the start.
Eija holds a PhD from the Medical faculty of University of Adelaide, Australia, and she completed her post doctoral research as an EMBO long term fellow in the University of Helsinki, Finland. Eija has over 40 peer-reviewed publications and an H-index of 21.
This workshop 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 gene expression analysis. The workshop consists of lectures and practical exercises. The free and user-friendly Chipster software is used in the exercises, so no previous knowledge of Unix or R is required, and the workshop is thus suitable for everybody.
[The lectures are available as videos, and the participants are requested to view them prior to the workshop. This gives you more time to reflect on the concepts so that you can use the workshop time more efficiently. The lectures are summarized, and questions answered during the workshop].
You will learn how to
-check the quality of reads with FastQC
-infer strandedness with RseQC
-align RNA-seq reads to the reference genome with HISAT2 and STAR
-perform alignment level quality control using RseQC
-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