3 Compensation Mistakes That Will Ruin Your Flow Cytometry Experiments

Putting it basically, compensation is the mathematical process of correcting spectral spillover from a fluorochrome into a secondary detector. Yet even the most talented rookie researchers may find themselves at a loss when it comes to this topic. This is one of the most important parts of the experiment to get correct, and yet there remain rumors and myths that circulate among users that will prevent you from getting correct compensation.

Good compensation requires that you tightly adhere to certain rules, understand the function of your instrument, and keep in mind how fluorescence occurs. Compensating poorly leads to false conclusions, and you certainly don’t want that.

Even among us flow cytometry veterans, a strong foundation is occasionally in need of a tune-up. And in a topic as dense as flow cytometry, it’s important that we refresh ourselves on some of the fundamentals once in a while. In fact, it is the longtime cytometry expert who must check themselves for any sort of faith in faulty old practices. Science is ever a work in progress, and traditional methods are not always the right methods.

Today’s blog will review 3 incorrect concepts that continue to circulate around this important process and why you want to avoid them.

Compensation Principles, Redux

To start, let’s quickly cover a few ground rules for good compensation. As you perform your own experiments, remember these founding principles:

  • Your control must be (at least) as bright as your sample.
  • The backgrounds of the positive and negative carriers must be matched.
  • Compensation color must precisely match experimental color

Compensation ultimately is the calculation of the slope of the line between a single stained positive and an unstained negative. If the particles are too dim, the resulting slope value will fall well below where it ought to be. Thus, the control has to match the sample’s brightness. Make sure the controls are bright and treated the same way. Remember also that signals need to be on-scale and within the linear region of the PMT detector. When a signal violates either of these conditions, accurate compensation becomes impossible.

Additionally, to properly calculate slope, the positive and negative backgrounds must be the same – otherwise, you’re lacking a control setting for accurate comparison. Finally, compensation color has to exactly match the experimental color. You’ll want a matched fluorochrome, matched sensitivity, and matched treatment. Otherwise, you’re dealing with different spectra, and you won’t be able to substitute one for the other.

3 Mistakes That Negatively Impact Flow Cytometry Experiments

Now that we’ve covered some proper methodology, let’s get to the 3 faulty methods that will bring confusion and inaccuracy to any flow cytometry experiment. Avoid the following practices at all costs.

1. Incorrectly employing a universal negative

The “universal negative” refers to a process in which a single tube, consisting of unstained cells, sets the negative population for establishing the compensation matrix. If you only have beads, or you only have cells, then a universal negative can be used without issue. As an example, if you were to use beads as a positive control in your experiment, the correct comparison would be unstained beads. However, if you have a mixture of beads and cells, then you must avoid a universal negative. What you don’t want is to use cells as a negative control with beads as your positive control. Figure 1 shows the impact of mismatched controls.

Figure 1: Unstained cells (green) and unstained beads (purple) are matched with positively stained beads. The lines connect the positive bead median with the medians of the negative populations.

If you want accurate results, positive and negative carriers must have the same background. For example, if you had beads for the antibodies and cells for, say, DAPI or GFP, you’d need a positive sample and a negative sample for each control. In fact, the best practice is to have a positive and a negative sample in each of your compensation controls. This ensures that samples are treated identically through the staining process.

2. Preventing compensation values from exceeding a certain percentage.

You might have heard a rumor that compensation ought to be no greater than a set amount. Specifically, you might have heard it said that this amount is around the 40-50% range. But remember that compensation consists of a mathematical correction that is based on appropriate controls. What can follow from this faulty line of thinking is the impression that compensation values need to be reduced – in other words, that the voltage ought to be adjusted. This is a waste of effort. Changing the voltage will impact the compensation value, but it has no effect on your data spread., as shown in Figure 2.

Figure 2: Spreading error is independent of compensation value. PE and PE-Cy5 were collected over a range of voltages for the PE-Cy5 detector while holding the PE detector voltage constant. Compensation values for each voltage were calculated in FlowJo yielding values ranging from 2.7% up to 2,900%. Importantly, the spread of the PE-Cy5 beads in the PE channel as indicated by the dashed line is unchanged. This data shows that a high compensation value is not indicative of severe spillover spreading. Data courtesy of the University of Wisconsin Carbone Cancer Center Flow Cytometry Lab.

Any spreading error is independent of your compensation value, so you may rest assured that a high compensation percentage does not indicate any sort of severe spillover issue. As far as voltage adjustment, what you should actually aim for is voltration. This is the optimization of voltage achieved using a “voltage walk.” Importantly, this process needs to occur during panel optimization. During voltration, correctly titered antibodies will stain cells, and these get run at increasing voltages. Then the Staining Index is calculated and the optimal point of antibody separation can be identified.

3. Reusing a compensation matrix

Not every experiment goes according to plan. Sometimes, an experiment is skewed by some error or another. You might be able to salvage these experiments, but what if the controls are lost? Sometimes, the experimenter decides to be “efficient” by reusing the matrix from a previous experiment. For some reason, this is an idea that researchers continue to bring to the table – but it’s not a good idea.

In order for compensation to be accurate, the setting and fluorochrome must be identical. By using a matrix from a previous experiment, you are violating that critical staple of the calculation process. What if a previous experiment ran a dye that sticks? Or what if the instrument had a major realignment or repair conducted? These issues could compromise your data.

With the relatively low cost of capture beads and the fact that you don’t need to use the same concentration of antibody as on your samples, there is no excuse to reuse a matrix in an attempt to save a few minutes on this essential control. Figure 3 shows how a compensation matrix acquired one week apart change. The instrument was under tight control, and the voltages based on application-specific settings, coupled with using peak 6 beads to check voltage.

Figure 3: Beads were stained with antibodies and acquired on a FACSCanto-II. The compensation matrix was calculated in Flowjo. The percentage difference between week 1 and week 2 was calculated. As can be seen, there are significant differences between the matrices.

In conclusion, poor or incorrect compensation is naturally deleterious to the reliability of your data. So as you go about your experiments in the future, you can facilitate high-quality compensation by following the ground rules outlined and avoiding these 3 major errors that researchers sometimes make: incorrectly employing a universal negative, preventing compensation values from exceeding a certain value, or reusing a compensation matrix.

As a final note, if there are issues with your data, avoid the temptation to manually adjust the compensation matrix – especially to make the data “look right.” Instead, figure out what is causing compensation problems by reviewing the data in the context of this guide. And in general, make sure that a standard reference control is always run in the panel. This allows you to evaluate the whole staining process, and it helps the troubleshooting process when compensation seems problematic.

To learn more about compensation mistakes and get access to all of our advanced materials including 20 training videos, presentations, workbooks, and private group membership, get on the Flow Cytometry Mastery Class wait list.

Join Expert Cytometry's Mastery Class
Tim Bushnell, PhD
Tim Bushnell, PhD

Tim Bushnell holds a PhD in Biology from the Rensselaer Polytechnic Institute. He is a co-founder of—and didactic mind behind—ExCyte, the world’s leading flow cytometry training company, which organization boasts a veritable library of in-the-lab resources on sequencing, microscopy, and related topics in the life sciences.

Similar Articles

The 5 Fundamental Methods For Imaging Nucleic Acids

The 5 Fundamental Methods For Imaging Nucleic Acids

By: Heather Brown-Harding, PhD

There are 4 major ways to sort cells. The first way can use magnetic beads coupled to antibodies and pass the cells through a magnetic field. The labeled cells will stick, and the unlabeled cells will remain in the supernatant. The second way is to use some sort of mechanical force like a flapper or air stream that separates the target cells from the bulk population. The third way is the recently introduced microfluidics sorter, which uses microfluidics channels to isolate the target cells. The last method, which is the most common––based on Fuwyler’s work––is the electrostatic cell sorter. This…

Avoid Flow Cytometry Faux Pas: How To Set Voltage The Right Way

Avoid Flow Cytometry Faux Pas: How To Set Voltage The Right Way

By: Tim Bushnell, PhD

There are 4 major ways to sort cells. The first way can use magnetic beads coupled to antibodies and pass the cells through a magnetic field. The labeled cells will stick, and the unlabeled cells will remain in the supernatant. The second way is to use some sort of mechanical force like a flapper or air stream that separates the target cells from the bulk population. The third way is the recently introduced microfluidics sorter, which uses microfluidics channels to isolate the target cells. The last method, which is the most common––based on Fuwyler’s work––is the electrostatic cell sorter. This…

Designing Microscopy Experiments Related To Infectious Diseases And Antivirals

Designing Microscopy Experiments Related To Infectious Diseases And Antivirals

By: Heather Brown-Harding, PhD

There are 4 major ways to sort cells. The first way can use magnetic beads coupled to antibodies and pass the cells through a magnetic field. The labeled cells will stick, and the unlabeled cells will remain in the supernatant. The second way is to use some sort of mechanical force like a flapper or air stream that separates the target cells from the bulk population. The third way is the recently introduced microfluidics sorter, which uses microfluidics channels to isolate the target cells. The last method, which is the most common––based on Fuwyler’s work––is the electrostatic cell sorter. This…

My 3-Step Panel Validation Pocket Guide

My 3-Step Panel Validation Pocket Guide

By: Tim Bushnell, PhD

There are 4 major ways to sort cells. The first way can use magnetic beads coupled to antibodies and pass the cells through a magnetic field. The labeled cells will stick, and the unlabeled cells will remain in the supernatant. The second way is to use some sort of mechanical force like a flapper or air stream that separates the target cells from the bulk population. The third way is the recently introduced microfluidics sorter, which uses microfluidics channels to isolate the target cells. The last method, which is the most common––based on Fuwyler’s work––is the electrostatic cell sorter. This…

Easy-To-Forget Flow Fundamentals That Thwart Bad Science

Easy-To-Forget Flow Fundamentals That Thwart Bad Science

By: Tim Bushnell, PhD

There are 4 major ways to sort cells. The first way can use magnetic beads coupled to antibodies and pass the cells through a magnetic field. The labeled cells will stick, and the unlabeled cells will remain in the supernatant. The second way is to use some sort of mechanical force like a flapper or air stream that separates the target cells from the bulk population. The third way is the recently introduced microfluidics sorter, which uses microfluidics channels to isolate the target cells. The last method, which is the most common––based on Fuwyler’s work––is the electrostatic cell sorter. This…

Important Controls For Your Flow Cytometry Lab

Important Controls For Your Flow Cytometry Lab

By: Tim Bushnell, PhD

There are 4 major ways to sort cells. The first way can use magnetic beads coupled to antibodies and pass the cells through a magnetic field. The labeled cells will stick, and the unlabeled cells will remain in the supernatant. The second way is to use some sort of mechanical force like a flapper or air stream that separates the target cells from the bulk population. The third way is the recently introduced microfluidics sorter, which uses microfluidics channels to isolate the target cells. The last method, which is the most common––based on Fuwyler’s work––is the electrostatic cell sorter. This…

4 Factors To Improve Flow Cytometry Cell Sorting Speed

4 Factors To Improve Flow Cytometry Cell Sorting Speed

By: Tim Bushnell, PhD

There are 4 major ways to sort cells. The first way can use magnetic beads coupled to antibodies and pass the cells through a magnetic field. The labeled cells will stick, and the unlabeled cells will remain in the supernatant. The second way is to use some sort of mechanical force like a flapper or air stream that separates the target cells from the bulk population. The third way is the recently introduced microfluidics sorter, which uses microfluidics channels to isolate the target cells. The last method, which is the most common––based on Fuwyler’s work––is the electrostatic cell sorter. This…

5 Techniques For Dramatic Improvements In Reproducibility

5 Techniques For Dramatic Improvements In Reproducibility

By: Heather Brown-Harding, PhD

It’s not easy to improve reproducibility in your experiments. Image manipulation has become a major problem in science, whether intentional or accidental. This has exploded with the advent of digital imaging and software like Photoshop. There are even mobile applications like Instagram filters that can be used for imaging trickery. It should go without saying that image reuse/manipulation represents profound dishonesty in science – a field intended to uphold the most stringent possible standards of truthful inquiry! But what about studies with a sloppy or stunted capacity for reproduction? These, too, plague science and hinder our ability to seamlessly move…

Understanding Reproducibility in Flow Cytometry - It’s the Antibodies!

Understanding Reproducibility in Flow Cytometry - It’s the Antibodies!

By: Tim Bushnell, PhD

Reproducibility is key to the scientific method. After the results of a study are published, the community validates the findings and extends them. If the findings are not reproducible, the second step is impossible. With performable experiments increasing in complexity, and the concurrent increase in the cost of equipment and reagents to perform these experiments, it is important to find the best way to maximize the money spent on advancing research. In flow cytometry, there are many places where improvements can be made to increase the consistency and reproducibility of an experiment. The most obvious place is in the instrument,…

Top Technical Training eBooks

Get the Advanced Microscopy eBook

Get the Advanced Microscopy eBook

Heather Brown-Harding, PhD

Learn the best practices and advanced techniques across the diverse fields of microscopy, including instrumentation, experimental setup, image analysis, figure preparation, and more.

Get The Free Modern Flow Cytometry eBook

Get The Free Modern Flow Cytometry eBook

Tim Bushnell, PhD

Learn the best practices of flow cytometry experimentation, data analysis, figure preparation, antibody panel design, instrumentation and more.

Get The Free 4-10 Compensation eBook

Get The Free 4-10 Compensation eBook

Tim Bushnell, PhD

Advanced 4-10 Color Compensation, Learn strategies for designing advanced antibody compensation panels and how to use your compensation matrix to analyze your experimental data.