Single-Cell Analysis

This week-long course will cover the practicalities of single-cell sample prep and analysis with a particular focus on single-cell RNA-seq libraries. 

Course coordinators:

  • Dr. Susan Kloet (LUMC)
  • Dr. Miao-Ping Chien (Erasmus MC)
  • Dr. Ahmed Mahfouz (LUMC)

Course Credits:
The study load of this course is 2 ECTS credits. Participants will get a certificate after successfully completing this course.

Course overview:
The course features a mix of lectures and practicals, and you will have the opportunity to perform hands-on analysis of scRNA-seq data in R. Topics to be covered in the course include (but not limited to): an overview of different single cell platforms, experimental design, preprocessing of scRNA-seq data, normalization, dimensionality reduction, clustering, batch correction, differential expression, trajectory inference. The fifth day of the course will be a mini-symposium featuring guest lectures from scientists using various single-cell techniques in their research.

Target audience:
This course is aimed at both wet-lab researchers interested in learning how to analyze their own single-cell data sets, as well as bioinformaticians who are new to single-cell sequencing analysis. Basic knowledge of the programming language R is a prerequisite for participation in the course.

More information:
For more information about the course programme you can check the program from 2021 or contact dr. Ahmed Mahfouz.