This hands-on course in Zoom introduces single-cell RNA-seq (scRNA-seq) data analysis methods. It covers the processing of transcript counts from quality control and filtering to dimensional reduction, clustering, cell type identification and cluster marker gene detection. You will also learn how to do integrated analysis of multiple samples.PracticalitiesBoth course days are 9:00-12:30 Finnish time (8:00-11:30 CET).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 classroom time more efficiently for discussions and exercises.PrerequisitiesIn the exercises we use Seurat tools embedded in the free and user-friendly Chipster software, so no experience in R is required, and the course is thus suitable for everybody who is planning to use single-cell RNA-seq.ContentYou will learn how toperform quality control and filter out low quality cellsnormalize gene expression valuesremove unwanted sources of variationselect highly variable genes and perform dimensionality reduction (PCA)cluster cellsvisualize clusters using UMAP and tSNEidentify cell types using reference-based SingleRfind marker genes for a clusterintegrate multiple samplesfind conserved cluster marker genes for two samplesfind genes which are differentially expressed between two samples in a cell type specific mannervisualize genes with cell type specific responses in two samplesCourse materialsLinks to slides, lecture videos and exercisesTrainersMaria Lehtivaara, Eija Korpelainen and Iida Hakulinen (CSC)Price60 eurosMore informationShould you have any questions, please don't hesitate to contact [email protected].