Flow cytometry data analysis
Trainers: Katrien Quintelier and Yvan Saeys
Overview: The number of dimensions in cytometry experiments keeps increasing, which makes the traditional manual gating process infeasible. In this session, we will explore how to handle cytometry data in R and execute a complete computational pipeline, including quality control, batch effect removal and clustering.
Learning outcomes:
By the end of this session you will:
- Know the steps of a computational analysis pipeline and why and how you should implement them.
- Be able to evaluate the quality of your data.
- Understand a FlowSOM model and how to go from the model to a final conclusion.
Materials: