This hands-on course introduces single-cell RNA-seq (scRNA-seq) data analysis concepts and R packages. It covers the processing of transcript counts from quality control and filtering to dimensional reduction, clustering, cell type identification and differential expression analysis.

Practicalities

The course consists of lectures and exercises. Participants are requested to view the lecture 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 classroom time more efficiently for discussions and exercises. The lecture videos are kindly provided by NBIS, the Swedish Node of ELIXIR (for more information, please see the section "Course materials" here below).

Participants are selected based on motivation description in the application form. Some of the seats are reserved for Doctoral Program in Biomedicine (DPBM) students, whose participation fee is covered by the program.

Prerequisities

You should have some experience in using R. If you don't have these skills, you might like to attend the course Single cell RNA-seq data analysis with Chipster instead.

Content

Topics covered:

• quality control
• normalization
• removal of undesired sources of variation
• choosing variable genes
• dimensionality reduction
• clustering
• differential gene expression analysis
• integrating different datasets
• cell type identification

Trainers

Bishwa Ghimire, Laura Langohr, Matias Falco, Anna Pirttikoski (University of Helsinki)

Course materials

The code for exercises is available in Gitlab.

Before the course you need to watch the following lecture videos. The lectures are kindly provided by

• Åsa Björklund, Paulo Czarnewski and Olga Dethlefsen from National Bioinformatics Infrastucture Sweden (NBIS, ELIXIR-SE)
• Ahmed Mahfouz from Leiden University Medical Center, Netherlands

Module 2 Quality control: lectures 4, 6-8
Module 3 Normalization: lectures 1, 3-5
Module 4 Dimensionality reduction: lectures 1-5
Module 5 Data integration: lectures 1, 3-5
Module 6 Clustering: lectures 1-4, 8
Module 7 Differential expression: lectures 1-2, 4, 6
Module 8 Gene set analysis: lectures 1-3, 5
Module 9 Cell type prediction: lectures 1-5, 8

Slides and exercises will be shared during the course.

Price

60 euros including VAT.

Important dates

• application deadline 7.9.2022
• selection results announced 23.9.2022
• selected participants need to register by 30.9.2022