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.

In addition you can choose an optional spatial transcriptomics module, which takes place 25.10.2022 at 9:00 – 12:00. This module covers the analysis of Visium data.

Please note that you are most welcome to attend also the Single cell transcriptomics symposium in Biomedicum Helsinki 5.10.2022.

Practicalities

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.

Prerequisities

In 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.

Content

You will learn how to

• perform quality control and filter out low quality cells
• normalize gene expression values
• remove unwanted sources of variation
• select highly variable genes and perform dimensionality reduction (PCA)
• cluster cells
• visualize clusters using UMAP and tSNE
• identify cell types
• find marker genes for a cluster
• integrate multiple samples
• find conserved cluster marker genes for two samples
• find genes which are differentially expressed between two samples in a cell type specific manner
• visualize genes with cell type specific responses in two samples

During the optional spatial transcriptomics module on 25.10.2022 you will practise the corresponding analysis steps for Visium data. In addition you will learn how to 

• identify genes which have spatial patterning without taking clusters or spatial annotation into account
• subset out anatomical regions
• integrate spatial data with single-cell data

Course materials (slides, exercises, lecture videos)

• Single-cell RNA-seq data analysis
• Spatially resolved transcriptomics (Visium) data analysis

Trainers

Maria Lehtivaara, Eija Korpelainen and Iida Hakulinen (CSC)

Price

60 euros for 7.10.2022, additional 30 euros for the optional spatial transciptomics module on 25.10.2022.

More information

Should you have any questions, please don’t hesitate to contact chipster@csc.fi.