Video Tutorials
A collection of FlowJo Videos
Step-by-Step Tutorials
All tutorials include a PDF, a demonstration dataset, and completed workspaces.
The FlowJo Basic Tutorial
The Basic Tutorial gets you up to speed quickly with key concepts in FlowJo. A common titration experiment is used to demonstrate some of the basic analysis features of FlowJo. You can watch one of our application scientists demonstrate the Basic Tutorial (about 15 minutes).8 Color PBMC Experiment
Provides a in-depth overview of the main FlowJo functions in the context of a 'real world' data set. Includes an introduction to compensation and provides tips on speeding analysis thorough filtered batch operations.
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Cell Cycle Tutorial
Explains the Watson and the Dean, Jett, Fox cell cycle models used by FlowJo and provides stepwise instruction through two 2-color PBMC experiments.
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Proliferation Tutorial
Provides an overview of the proliferation modeling algorithm, suggests model adjustment techniques, and gives an explanation of the proliferation statistics in FlowJo.
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Kinetics Tutorial
Shows how to analyze time series data in FlowJo using a simple kinetics experiment.
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Batching and Iteration Tutorial
Grants you access to the most powerful tool in FlowJo, the iterated batch. Learn how to reduce analysis time and benefit from the patterns of your dataset(s).
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Tech Notes and Additional Data Sets
Antibody Panel Wizard
This tool provides a simple interface for instrument selection and configuration, and of target-fluorochrome refinement, using combined product databases from multiple major manufacturers. The Wizard checks fluorescence excitation/emission profiles, and matches target-fluorochrome combinations to the appropriate laser/detector of the instrument and automatically assigns fluorochromes to specific detectors based on their excitation and emissions profiles. Learn more at Fluorish.com.Compensation
This data set provides an introduction to performing compensation using FlowJo. Contains three single stain controls and one test sample. For more information on FlowJo's Compensation platform, click here For Mac - For Windows.Instrument Sensitivity - Q&B
Recent work at the National Institute for Standards and Technology (NIST) has established the first reference standards in an effort to improve quantitative fluorescence measurements. The most common terms for characterizing detector performance are Q & B. Q is the measure of detector efficiency. B is the the background light level, the number of photons measured when no cells are present. More... Please note: this platform is not yet public but will be coming soon.Calibration
This example illustrates how you can calibrate a parameter based on a standardized set of beads. For more information on FlowJo's Calibration platform, click here For Mac - For Windows.Full Immunophenotyping
The Full Immunophenotyping data set serves as an example of how a large experiment is analyzed and how the analyses are organized by FlowJo. The analyses depend largely on the "Group"-based operations in FlowJo, where entire sets of samples (i.e., all tubes wi.th the same stain combination) are gated identically. For more information on Groups, click here For Mac - For Windows.Complex Analysis
There is only a single data file in this example. It is a collection of 300,000 events of PBMC stained with 8 different antibody conjugates. The reagents used in this experiment are: Cascade Blue anti-CD3, FITC anti-CD11a, PE anti-TcR gd, Cy5PE anti-CD45RA, Cy7PE anti-CD62L, Texas Red anti-CD4, APC anti-CD57, and Cy7APC anti-CD8. The goal in this stain was to identify fine T cell subsets.11 Color Demonstration
There is only a single data file in this example. It is a collection of 300,000 events of PBMC stained with 8 different antibody conjugates. The reagents used in this experiment are: Cascade Blue anti-CD3, FITC anti-CD11a, PE anti-TcR gd, Cy5PE anti-CD45RA, Cy7PE anti-CD62L, Texas Red anti-CD4, APC anti-CD57, and Cy7APC anti-CD8. The goal in this stain was to identify fine T cell subsets.Large Data File
A single PBMC sample was stained with antibodies to CD3, CD4, and CD8. The sample was collect four times, with increasing numbers of events: 1000, 10,000, 100,000, and 1 million. Using these data files, you can explore how different types of displays can be dramatically different even though essentially the same data is being viewed.
