What does FlowJo do?
FlowJo software loads flow cytometry data and facilitates complex data analysis for flow experiments. FlowJo is very powerful, and can be used for many different types of experiments (outlined in our online manual). Tutorials.
FlowJo analyzes data collected by a flow cytometer (data from the cytometer must be saved as an fcs compliant file). FlowJo’s strength is in analyzing whole experiments encompassing many related samples. In addition to gating and statistics, FlowJo also can analyze DNA/Cell Cycle, Kinetics, and Proliferation Experiments. FlowJo has sophisticated tools for generating statistics, graphs, tables, webpages, and even movies.
Experiments and workspaces
An experiment can be a single collection of samples, or it can stretch across multiple collections over a period of months.
FlowJo organizes experiments as a collection of samples in a workspace. The workspace shows the hierarchical tree of sample populations (gates) and statistics that are created in the analysis. You can close the workspace, and then reopen in the future and start where you left off. You can have multiple workspaces open at the same time and drag-drop samples and gates between workspaces.
Within a workspace, you can group samples by various attributes. For instance, you can make a group of samples with similarly stains, or group samples by Patient, etc. Groups are a powerful feature of FlowJo: when you perform an operation on a group, it performs the operation on every sample belonging to that group. Thus, you can apply a gate or a statistic to a group, causing that gate or statistic to be automatically performed on all samples in the group.
Analyzing with FlowJo
You will find that your mode of operating FlowJo will probably be very similar to the following series of steps:
Load the samples into a workspace.
Create Groups for related.
Analyze a single sample in detail, creating gates, statistics, etc.
Apply the appropriate analyses to all the samples in a group.
Check gates on the samples in the group: modifications to accommodate sample to sample variation are easily made.
Generate a graphical layout in which you can display particular graphs from all samples.
Generate a table in which you can create particular statistics from all samples.
If you do similar experiments with different Patients, you can then save a workspace as a template containing all the gates and statistics and tables and layouts... Next week, when you do the same experiment with different Patients, most of the work is already done for you! You simply have to import the new samples into the template workspace. Good template design saves a huge amount of software analysis time and standardizes reporting.
The Gating Hierarchy
Another fundamental concept in FlowJo is that of the gating hierarchy. When you first generate a gate on a sample (for instance, a lymphocyte gate), FlowJo shows you this gate (subset population) in the paradigm of a genealogical tree. In other words, the Lymphocyte subset is a child of the parent sample. It is shown in the workspace underneath the sample, indented a single level from the sample. If you were to make another gate on the sample (for instance, monocytes) FlowJo will create another new subset as another child of the sample; now, the lymphocyte and monocyte gates are siblings.
Any operation that you can perform on a sample can also be performed on a subset of the sample. Therefore, you can view the lymphocyte subset and create gates (subsets) of this population. If you create a T cell gate within lymphocytes, then the T cell subset becomes a child of the lymphocytes (and, by extension, a grandchild of the sample).
Batch operations
Batch operations (repetitive analyses performed on multiple samples) can be used in creating layouts and tables in FlowJo. In general, batch operations are performed on all samples in the current group (therefore, you will want to create sample groups that will serve to help you generate batch outputs).
In this way, FlowJo is a program that doesn't just analyze individual data samples. Rather, the focus is on analyzing groups of samples, experiments, or even multiple experiments at once.
Compensation
Spectral overlap of stains is dealt with in the compensation tool in FlowJo. An interface for computing the compensation matrix based on a collection of singly-stained control samples. You can then apply this compensation matrix to multi–stained samples. FlowJo adds compensated parameters to the multi-stained samples so you can view and analyze compensated data.
Derived Parameters
FlowJo lets you define new parameters for samples. These may include scaling parameters (to blow up a region of interest), Time (for performing kinetics analyses), a ratio parameter, or a parameter to convert between log and linear scaling. Derived parameter definitions can be copied to entire groups of samples.
Kinetics (Ca++ flux) analyses
FlowJo provides a sophisticated platform designed to analyze kinetics data. FlowJo looks for a parameter that corresponds to time (and is named "Time"); if it does not, FlowJo allows you to create a time parameter (assuming a constant event rate). From the Kinetics platform, you can compute the maximal response time, the slope of a response, the fraction of responding cells, etc.
Cell Cycle Analysis
FlowJo has a Cell Cycle Platform that uses multiple models to fit the data, constrain the fitting parameters, and automatically calculate the percentage of cells in G1, S, or G2 phases. All models can be copied to other populations or samples, with the same easy drag and drop interface used to propagate other gates or analyses.
Calibration (Quantitation)
FlowJo has a unique Calibration Platform that allows you to calibrate any collected parameter. Most commonly, this is used to convert the scaling into absolute number of molecules (given a standard that converts between the fluorescence intensity collected on your instrument and absolute numbers of fluorophores). The platform can use a calibrated bead set as a standard, a stained sample as a reference, or numbers that you enter to define the calibration manually.
Proliferation Analysis
The Proliferation Platform is used to model proliferation data obtained using cell tracking dyes such as CFSE. FlowJo presents a graphical display as well as information about each generation in the subset. The proliferation platform also provides information about the fraction of cells from the original population that have divided, and the number of times these cells have divided. In addition the FlowJo Proliferation Platform draws gates that separate each generation.
Movies
Movies. An analysis platform unique to FlowJo: view your data dynamically. Use the Movie Platform to generate graphs as a function of time (kinetic analyses), or to generate a graph of one or two parameters as a function of a third. This unique visualization lets you uncover subtle relationships in your data that would be impossible to see otherwise.
Backgating Analysis
Once your analysis contains subpopulations produced by gating within gates, it can be useful to see the source of a given subpopulation rendered graphically. Backgating analysis shows graphs of each gating operation with the final subpopulation highlighted in the graph of each stage.
Statistics and Formulas
A host of standard statistical calculations can be performed on a subpopulation then generalized to the whole experiment by batching. FlowJo will build a table of statistical analyses across groups of samples that you designate. These tables update continuously as long as you are modifying your experiment. For example, changes to gates will cause any statistic associated with the gate to update. You can export tables to spreadsheets or databases. You can also devise and apply your own formulas within FlowJo and use its tools to complete your analysis across multiple populations without tedious duplication of effort. The tables you create can be dragged and dropped from one workspace to another.
