Course Flow cytometry

The course B69/32 Flow cytometry is being offered by the Graduate School of Health, Aarhus University, 2023.

Criteria for participation: University degree in medicine, dentistry, nursing, or master’s degree in other fields and/or postgraduate research fellows (PhD students and research-year medical students).

Recommended knowledge for participation: The literature suggested in the detailed program is recommended prior reading.

Aim: The aim of the course is to provide a solid theoretical and practical foundation in modern flow cytometry, enabling participants to assess and conduct flow cytometric experiments independently.

Learning outcomes: 

1. Understanding the physics behind flow cytometry
2. Understanding the applications and limitations of flow cytometry
3. Practical knowledge and experience with flow cytometry experiment design
4. Understanding essential flow cytometry controls
5. Awareness of common (and not so common) pitfalls
6. Hands-on, practical experience with data analysis
7. Ability to critically evaluate flow cytometry results
8. Requirements for publication of flow cytometry experiments

Workload: The full workload of the course is expected to be 57 hours.

Content: In contrast to most basic flow cytometry courses and online resources, this intensive training course teaches key concepts by derivation from "first principles". The course thus covers the progression from the basic physics of light and fluorescence, through fluorochrome chemistry, spectral overlap and compensation, and antibody panel design, experiment design, flow cytometry controls, and data analysis. On the instrumentation side, the course provides a detailed understanding of the core components in modern flow cytometers, thus covering light detection principles, fluidics, optics and signal processing. Data analysis and compensation is taught by a "hands-on" approach via practical computer exercises with FlowJo software and generic, raw flow cytometry data files (participants are encouraged to bring their own PC and data, if relevant). Advanced data analysis approaches (clustering, dimensionality reduction, tSNE and more) are presented in the last part of the course. In addition, guidelines for publishing flow cytometry data will be covered.

Instructors: Charlotte Christie Petersen, Anja Bille Bohn and Mikkel Steen Petersen

Venue: Arhus University, Aarhus

Participation in the course is without cost for:

• PhD students, Health Research Year students and Health Research Honours Programme students from Aarhus University
• PhD students enrolled at partner universities of the Nordoc collaboration
• PhD students from other institutions in the open market agreement for PhD courses

Course dates:

• 25 September 2023 08:30 - 15:15
• 26 September 2023 08:30 - 15:30
• 27 September 2023 08:30 - 15:45
• 28 September 2023 08:30 - 15:00
• 29 September 2023 08:30 - 14:15