FlowJo for flow cytometry analysis
FlowJo for flow cytometry analysis
11 December 2026, 9h30- 17h00
General context
Are you a researcher working with flow cytometry data?
This introductory FlowJo course is designed to help you get started with one of the most widely used analysis tools in the field. With the release of FlowJo Version 11—now available on Windows and macOS—users benefit from a streamlined, intuitive interface that simplifies complex data analysis. This training will guide you through the core functionalities of the software, helping you build confidence in gating strategies, population analysis, and data visualization. By the end of the session, you’ll be equipped to independently analyze your own datasets and integrate FlowJo into your research workflow.
- Identify the main components of the FlowJo Version 11 interface and describe their functions.
- Import and organize flow cytometry data files within FlowJo for efficient analysis.
- Apply basic gating strategies to define and analyze cell populations.
- Interpret graphical outputs such as histograms and dot plots to conclude cytometry data.
- Demonstrate the ability to save, export, and document analysis results for reporting and collaboration.
The course combines short theoretical lectures with hands-on analysis of an example dataset in FlowJo.
Prior knowledge of general flow cytometry is required, but the general principles will be repeated.
This course is part of the learning paths on Flow cytometry data.
AI methods used
FlowJo primarily relies on established statistical and data-driven methods rather than core AI or machine learning approaches. Through plugins such as FlowSOM, Phenograph, and UMAP, it incorporates machine learning–based clustering and dimensionality reduction methods to support the identification and visualization of cell populations in high-dimensional data.
Trainers
Gert Van Isterdael
As head of the VIB Flow Core, Gert provides flow cytometry expertise to the users of the core facility by giving technical help to the scientists, maintaining the machines, implicating high quality SOPs as well as providing both experimental setup and data analysis consultations. The Flow Core develops novel automated analysis techniques for multi-parameter flow cytometry data to remove user bias in close collaboration with the on-site Bioinformatics team headed by Prof. Yvan Saeys.
Sofie Van Gassen
Sofie is Postdoc at Ghent University working on optimization of the analysis of flow cytometry data by developing suitable machine learning algorithms. She's the creator of the FlowSOM algorithm.
Program
- Flow cytometry, multicolor flow, and compensation: general principles
- General layout introduction
- Workspace overview
- Creating, handling, and saving workspaces
- Creation of groups
- Gating procedures
- Creating statistics tables with the Table editor
- Data visualization with Layout editor
- Batch analysis features
- Automated compensation
- Practical exercise with some datasets
Practical info
11 December 2026
Ghent - VIB/UGent FSVM II
Technologiepark 75
9052 Zwijnaarde
Belgium
11 December 2026
Ghent - VIB/UGent FSVM II
From Ghent Sint-Pieters station, you can take a bus to Technologiepark. Please check Routeplanner De Lijn for schedules.
11 December 2026
Ghent - VIB/UGent FSVM II
Looking for a custom cycling route? Try the online cycling route planner to easily and quickly identify the fastest, safest and/or most scenic route to any destination in Ghent.
Cycling route planner
Shared bicycles:
Several providers are active in the area.
Take a look at their platforms:
- Indigo Weel Pro app
- Bluebike
- DOTT
- BOLT eBikes
- Donkey Republic
There are also some public bicycle pumps at the park.
11 December 2026
Ghent - VIB/UGent FSVM II
There is only one entrance to Technologiepark. At the entrance, please take a ticket - Parking is only allowed in regular parking spots (for instance in front of the building) and in the parking tower. Parking alongside the roads or in other places where there is no regular parking is prohibited.