|Date:||28.09.2017 9:00 - 29.09.2017 17:00|
|Location details:||The event is organised at the CSC Training Facilities located in the premises of CSC at Keilaranta 14, Espoo, Finland. The best way to reach us is by public transportation; more detailed travel tips are available.|
|Lecturers:|| Tallulah Andrews (Sanger Institute) |
Jenni Westoby (Sanger Institute)
Gioele La Manno (Karolinska Institutet)
Maria Lehtivaara (CSC)
Eija Korpelainen (CSC)
|Price:||The registration fee is 60 euros + VAT per day, and it includes morning and afternoon coffees. DPBM graduate school students register for free using their DPBM course form. Others register using the green button below.|
Payment can be made with electronic invoicing, credit card, or direct bank transfer. Note that for electronic invoicing you need the operator and e-invoicing address (OVT code) of your organization. Please also note that invoice reference is needed for electronic invoicing in your organization, so please have this available when registering.
This hands-on course introduces the participants to single-cell RNA-seq data analysis concepts and tools. It consists of two alternative days which cater for different levels of computational skills. Depending on your background, please choose
28.9. Single cell RNA-seq data analysis with R (previous experience of R and Unix required)
29.9. Single cell RNA-seq data analysis with Chipster (no prerequisites, this day is suitable for everybody)
The content and prerequisites of these course days are described in more detail below. Please note that you can also participate in the Single Cell Symposium on 27.9. The symposium takes place in Biomedicum 1 (Meilahti campus, Helsinki) and you can register here. Both the course and the symposium are organized in collaboration with the Doctoral Programme in Biomedicine (DPBM) of University of Helsinki.
28.9. Single cell RNA-seq data analysis with R
Content: This course focuses on the analysis steps which are performed once we have a digital expression matrix. It covers cell quality control, normalization and batch effect correction, as well as downstream analysis such as feature selection, clustering and pseudotime analysis. The Scater package for R is used in the hands-on exercises. Teaching is provided by Tallulah Andrews and Jenni Westoby from the Sanger Institute.
Prerequisites: This course is intended for those who have basic familiarity with Unix and the R scripting language.We will assume that you are familiar with mapping and analysing bulk RNA-seq data.
29.9. Single cell RNA-seq data analysis with Chipster
Content: You will learn to preprocess DropSeq data (from raw reads in FASTQ files into a digital gene expression matrix) and how to do clustering analysis and find cluster marker genes with Seurat tools (10X Genomics data used in the exercises). Teaching is provided by Eija Korpelainen and Maria Lehtivaara, CSC. There is also going to be an introductory lecture about machine learning by Gioele La Manno, Karolinska Institutet.
Prerequisites: As the user-friendly Chipster software is used in the exercises, no previous knowledge of Unix or R is required, and this course is thus suitable for everybody.