Flow Cytometry Analysis — Gates & Regions
Author: Mike Blundell | Reviewer: Chloe Fenton
Flow cytometry data analysis is fundamentally based upon the principle of gating. Gates and regions are placed around populations of cells with common characteristics, usually forward scatter, side scatter, and marker expression, to investigate and to quantify these populations of interest. Here we will show what the common flow cytometry graph outputs look like and how in a few simple steps you can identify different cell populations that have been stained with antibodies conjugated to fluorophores. In addition to this guide to flow cytometry, we have a handy PDF available to download on our gates, plots, and regions page, which can be used as a quick reminder.
How to Gate
Distinguishing Cell Populations Using Scatter Properties
The first step in gating is often distinguishing populations of cells based on their forward and side scatter properties. Forward and side scatter give an estimation of the size and granularity of the cells, respectively, although this can depend on several factors such as the sample, the wavelength of the laser, the collection angle, and the refractive index of the sample and the sheath fluid.
Simple Versus Complex Samples
Distinguishing populations of cells can be relatively straightforward for cell lines where there is only one type of cell, but it can be more complex for samples where there are multiple cell types.
Identifying Cell Populations in Whole Blood
As can be seen in the density plots in Figure 13, red cell lysed whole blood has several distinct populations. The red/yellow/green/blue hot spots indicate increasing numbers of events resulting from discrete populations of cells. The light scatter patterns of granulocytes, monocytes, and lymphocytes allow them to be distinguished from cellular debris and dead cells.
Excluding Debris and Dead Cells
Debris and dead cells often have a lower level of forward scatter and are found at the bottom left corner of the density plot. The forward scatter threshold can be increased to avoid collecting these events, or they can be removed by gating on the populations of interest (Figure 13A).
Combining Scatter and Fluorescence Data
Data can also be plotted as a combination of fluorescence and forward or side scatter as seen with CD45 Pacific Blue in Figure 13B.
Limitations of Scatter‑Only Gating
Forward and side scatter gating is often used to remove dead cells, which have increased autofluorescence and nonspecific binding of antibodies. However, including a viability dye is a much more reliable method.
Fig. 13. Analysis of lysed whole blood. A. SSC vs. FSC density plot, B. SSC vs. CD45 PB (MCA87PB) fluorescence plot. FSC, forward scatter; PB, Pacific Blue; SSC, side scatter.
Displaying Flow Cytometry Data Using Different Plot Types
In addition to density plots, events can be displayed as a dot plot, where no density information is shown, or as a contour map to show the relative intensity of scatter patterns. Examples of contour maps are shown in Figure 14.
Fig. 14. Analysis of lysed whole blood. A. SSC vs. FSC contour plot, B. SSC vs. FSC contour plot plus outliers. FSC, forward scatter; SSC, side scatter.
It is down to the user preference as to which display is preferred, but sometimes discrete populations of cells are easier to visualize on contour diagrams.
Frequently Asked Questions (FAQs)
What are gates and regions in flow cytometry?
Gates and regions are defined areas placed on flow cytometry plots to identify, analyze, and quantify specific cell populations that share common characteristics, such as size, granularity, or marker expression. They allow researchers to focus their analysis on populations of interest while excluding irrelevant events like debris.
Why is gating important in flow cytometry data analysis?
Gating is fundamental because it enables accurate identification and quantification of distinct cell populations within complex samples. By applying gates, researchers can separate meaningful biological signals from background noise, dead cells, or debris, improving data reliability and interpretation.
What is typically the first step in gating a flow cytometry experiment?
The first step in gating is usually separating cells based on forward scatter (FSC) and side scatter (SSC), which provide estimates of cell size and granularity. This initial gate helps distinguish cell populations from debris and noncellular events before further analysis.
What do forward scatter (FSC) and side scatter (SSC) represent?
Forward scatter correlates mainly with cell size, while side scatter reflects cell granularity or internal complexity. Together, FSC and SSC provide a foundational way to visually separate different cell types in a sample, such as lymphocytes, monocytes, and granulocytes.
How can dead cells and debris be excluded during gating?
Dead cells and debris are often excluded by applying FSC/SSC gates that remove low scatter events, which typically appear in the lower left of scatter plots. While scatter based gating can help, using a viability dye is a more reliable method for identifying and excluding dead cells.
What types of plots are used for gating in flow cytometry?
Common plot types include dot plots, density plots, contour plots, and histograms. Density and contour plots are especially useful for visualizing event frequency and identifying populations in complex samples, while dot plots show individual events without density information.
Can fluorescence data be used alongside scatter for gating?
Yes. Fluorescence parameters can be plotted against FSC or SSC to further refine gating strategies. For example, combining fluorescence from antibody-conjugated markers with scatter data helps identify specific immune cell subsets within heterogeneous samples.
Are gating strategies the same for all sample types?
No. Gating strategies vary depending on the sample and experiment. Cell lines with a single population are usually simpler to gate, while complex samples such as whole blood require multiple gating steps to distinguish different cell types and remove unwanted events.
What factors can influence FSC and SSC measurements?
FSC and SSC signals can be affected by several factors, including the sample type, laser wavelength, collection angle, and the refractive index of both the sample and the sheath fluid. These variables should be considered during experiment setup and data interpretation.
Is there a quick reference available for gates, plots, and regions?
Yes. Bio-Rad provides a downloadable PDF guide on gates, plots, and regions that serves as a convenient reference for common flow cytometry analysis methods and gating strategies.
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Resources
Bio-Rad is committed to helping you succeed in Flow Cytometry by sharing knowledge and best practices from our experts. Below are some extremely useful resources to enhance your journey of discovery and support your success.