Advanced Flow Cytometry Data Analysis Course
Overview
In recent years, many mathematically complex analysis algorithms have been introduced and have become a required part of the standard repertoire of flow cytometry data analysis techniques. In spite of their increasing use, the theory behind these methodologies remains opaque to many people in the cytometry community. This course intends to bridge this gap and provide cytometrists with the conceptual understanding that they need in order to navigate the wide array of new techniques out there.
The course is considered an “in depth introduction”. The mathematical theory behind the various techniques will be introduced in a way that is accessible to an average cytometrist. Particular emphasis will be placed on conceptual understanding of the algorithms and the effects of user specified inputs, so practitioners can understand how changing these parameters is affecting the outcomes.
Each day will be divided into two sessions with a break in the middle.
From 9AM – 12PM there will be theoretical talks regarding the algorithms.
From 12PM – 2PM there will be free time to allow for unstructured discussion, analysis of your own data or just free time to catch up on other activities.
From 2PM – 5PM There will be theoretical talks regarding the algorithms. Depending on the time, we will also have practical sessions applying the algorithms to sample data either provided by us or that you bring from your own lab,
Prerequisites
Experience with conventional analysis (i.e. gating) of flow cytometry. We will not be reviewing any of the basics. An understanding of flow cytometry experiment design, instrument configuration and optimization (including standard compensation) and data analysis is presumed.
You must also bring your own computer for data analysis purposes. Outlets to plug in your computer will be provided.
"As a participant of the inaugural workshop I highly recommend it for anyone with non-computational background interested in better understanding how the most commonly used algorithms actually work. It also a great opportunity to meet likeminded people."
Oleg Kolupaev - Flow Cytometry Researcher - UNC Chapel Hill
"It was a great lecture with so many interesting discussions. I learned a lot. I was enjoying breakfast and lunch time- tasty food and great fellows.I highly recommend this course to my friends/colleagues/flow-ers. Thank you, David :)"
Enzi Jiang - Senior Scientist - CSL Behring
"This was a fantastic opportunity that I am grateful to have been part of. I greatly expanded my understanding of high dimensional analytical theory as well as practical application and found the individualized support to be very useful for the entire group to succeed. The class size was perfect, and the amenities provided as well as the variety of options in the immediate local area allowed time to focus on the material. Thank you again for everything that was set up!"
Sarah Cassanova - Oncology Flow Core Manager - Jannsen Pharmaceutical Companies
"Thank you very much for the course; the material was excellent for someone like me who has until this point been confused by the available options for clustering and high dimensionality reduction. The overall experience was also fantastic, being able to find restaurants with excellent food that we could enjoy with other participants in the course."
Tom Ramos - Staff Scientist - City of Hope
"This is a top-quality course, that dives deep on fundamentals of data analysis. We learned an enormous amount of information and had stimulating discussions on best practices. Highly recommended! "
Diana Bonilla Escobar - Global Scientific Director - Cytek Biosciences
Instructors
The primary instructor will be Dr. David Novo.
Dr. Novo has over 25 years of experience in the field of flow cytometry data analysis. As the founder and creator of the popular flow cytometry data analysis software FCS Express, Dr. Novo has participated in implementing almost every data analysis algorithm commonly used in flow cytometry. Dr. Novo is familiar with both the practical requirements of end users, and the detailed mathematical underpinnings of the most complex algorithms.
Dr. Novo has presented and taught on a wide variety of topics throughout his career and excels in presenting complex topics in an accessible and meaningful way.
For the practical portion of the course, there will be several experienced data analysts to assist in using various software packages and trying out different algorithms.
February 26 - 27, 2026
$400 ** includes breakfast and lunch. There is a 10% discount for FlowTex attendees, see FAQ below
The class will be limited to 30 students.
February 26 - AM – Data Preprocessing
- Introduction to terminology and concepts
- Data Cleaning
- FlowCut
- FlowAI
- Data Scaling
- Downsampling
- Explanation of various algorithms
- Effects of different downsampling algorithms on downstream results
- Introduction to data analysis pipelines
February 26 PM – Dimensionality Reduction Algorithms
- Definition of Dimensionality reduction algorithms
- UMAP and TSNE – mathematical and conceptual underpinnings
- UMAP and TSNE – similarities and differences
- Time Permitting - Overview of Phate – comparison to UMAP and TSNE
February 27 AM– Clustering Algorithms
- Concepts common to all clustering algorithms
- In depth discussion of KMeans and Hiearchical Clustering
- Overclustering and cluster merging
- Phenograph
- SPADE and FLOWSOM
- Methods of viewing and analyzing clustered data
February 27 PM – Spectral Cytometry and Unmixing
- What is spectral cytometry?
- Conceptual differences and similarities between conventional compensation and unmixing
- When and why is spectral cytometry superior to conventional
- Why different unmixing algorithms give different results on the same data?
- The role of auto-fluorescence in spectral unmixing
Note: the precise schedule above is subject to change, with topics rearranged on different days.
Baylor College of Medicine
Michael E. DeBakey Center
Rm M321, M423
1 Baylor Plaza
Houston, TX 77030
Is Food Included?
Breakfast and lunch will be provided. Please email dataanalysiscourse@denovoresearch.org for any special dietary restrictions.
Tea, coffee and water will be provided during the theoretical and practical parts of the course.
Is there a discount for FlowTex 2026 attendees?
Yes - FlowTex attendees get a 10% discount. Please use the code FlowTex2026 during the checkout process
Are there special hotel rates?
No special hotel rates have been reserved for this course. We have found that rates on common sites like Expedia etc. where often the same or cheaper than the "special rate" we were able to obtain from the hotel.
What software will we use?
FCS Express and Omiq will be provided to all attendees free of charge for use during the course. Experts will be available to assist with use of the software. Feel free to bring any other software you wish, however, we will not be able to provide any trouble shooting or specific technical support on any other software products.
Is there anything I need to do after I register?
In order to obtain a security badge, if you are not an employee/students of Texas Medical Center institutions, please send a photo of your drivers license to dataanalysiscourse@denovoresearch.org
Can I bring my own data?
We encourage participants to bring their own data. While the practical portion of the course will be using data provided by us we will attempt to work with you on your data between 12-2 or during the practical portion, time permitting.
Is Parking available?
The closest garage that is physically attached to Baylor College of Medicine is Garage 6, parking rate is currently $19/day. Rates may go up in 2026.
Participants are responsible for paying for their own parking fees.
How do I find the course once I arrive on campus?
If you do not have a TMC Institutional badge, you will have to go to the security desk and be escorted to the course. When you get to the security desk, email or call Claude Chew (I will send his contact info in a separate email).
If do TMC badge you can follow the directions below:
If entering from Garage 6:
- Check in at the security desk. You will be at the back of the main BCM building. Walk past the security desk and enter the building from the outdoor courtyard using the first door to your right. Take the 1st left and follow that long hallway all the way to the front of the building where it will dead-end.
- Turn right, follow that long hallway all the way until you see a set of 4 elevators on your left. You will be in the DeBakey Building now, which is where you want to be. Take the elevators to 3rd floor, on the first day, 4th floor on the second day and find room M321 on the first day and M423 on the second day. These rooms are located close to the elevators, if you have wandered down another long hallway, you are going the wrong way, turn back towards the elevators.
If entering from the main entrance (by the water fountain):
- Check in at the security desk, turn left when facing the security desk and take the long hallway until you see a set of 4 elevators on your left. You will be in the DeBakey Building now, which is where you want to be. Take the elevators to 3rd floor, on the first day, 4th floor on the second day and find room M321 on the first day and M423 on the second day. These rooms are located close to the elevators, if you have wandered down another long hallway, you are going the wrong way, turn back towards the elevators.
Can I get a refund if I cannot attend the course?
You can obtain a full refund if we can find someone else to take your spot in the course.
Is there a difference between this course and the 4 day course you offer?
Yes - there is a difference. While the syllabus looks similar, we will not be able to cover as much content as on the 4 day course. Also, the opportunity to try the different algorithms on your own data will be extremely limited, whereas on the 4 day course each afternoon is devoted to a practical component.
I have other questions, who can I contact?
Please email dataanalysiscourse@denovoresearch.org and we will be happy to answer any questions you have.
