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.PracticalitiesThe 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.PrerequisitiesYou 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.ContentTopics covered:quality controlnormalizationremoval of undesired sources of variationchoosing variable genesdimensionality reductionclusteringdifferential gene expression analysisintegrating different datasetscell type identificationTrainersBishwa Ghimire, Laura Langohr, Matias Falco, Anna Pirttikoski (University of Helsinki)Course materialsThe code for exercises is available in Gitlab.Before the course you need to watch the following lecture videos. The lectures are kindly provided byÅsa Björklund, Paulo Czarnewski and Olga Dethlefsen from National Bioinformatics Infrastucture Sweden (NBIS, ELIXIR-SE)Ahmed Mahfouz from Leiden University Medical Center, NetherlandsModule 2 Quality control: lectures 4, 6-8Module 3 Normalization: lectures 1, 3-5Module 4 Dimensionality reduction: lectures 1-5Module 5 Data integration: lectures 1, 3-5Module 6 Clustering: lectures 1-4, 8Module 7 Differential expression: lectures 1-2, 4, 6Module 8 Gene set analysis: lectures 1-3, 5Module 9 Cell type prediction: lectures 1-5, 8Slides and exercises will be shared during the course.Price60 euros including VAT.Important datesapplication deadline 7.9.2022selection results announced 23.9.2022selected participants need to register by 30.9.2022