Written by Tim Bushnell, Ph.D.
Compensation in flow cytometry is a critical step to ensure accurate interpretation of data. It is also one of the areas that’s steeped in mystery, myths and misinformation.
Before jumping into the best practices for compensation of flow cytometry experiments, it’s good to show what NOT to do when performing compensation.
Manually adjusting the compensation values based on how the populations look, or so-called ‘Cowboy Compensation’ (thanks to Joel Sederstrom for the term), is not the correct way to determine proper compensation.
For example, review the following figure, and ask yourself what is the best compensation value? This figure shows FITC on the Y-axis, spilling into the PE channel, on the X-axis…
Without knowing the median fluorescent intensity of the positives in the negative channel, or being able to evaluate the spread of the data, it is impossible to determine which of these above plots display the properly compensated values.
4 Steps To Compensating A 4-Color Experiment
The best practices for compensation involve following some very specific rules.These best practices also involve the use of automatic compensation protocols that are available in all major data analysis software packages.
(If you’re interested in following along with this blog, you can find the data used in this experiment at this link here.)
Step 1. Choose the correct carrier for compensation.
Compensation is a property of the fluorochrome you’re using in your experiments. The role of the carrier is to bring the fluorochrome to the laser intercept point.
The choice of the carrier is up to you, but for antibodies, the use of compensation beads is strongly recommended. Using beads offers several advantages for compensation, including…
- Cells are not wasted when preparing your compensation controls.
- All the antigen is captured in your solutions, not just some of it. This results in the brightest signal possible for your controls.
- Clear positive and negative signals show up on your control plots.
- Autofluorescence is not a factor since all the beads have the same autofluorescence values.
The biggest concern with preparing proper compensation controls is that the fluorescence intensity of the controls must be at least as bright as that of the cells that the compensation will be applied to. Conversely, the amount of antibody the beads are stained with is less critical.
Very often, compensation beads are stained with too much antibody and as a result, the fluorescent signal goes off-scale. When this happens, do NOT turn down the voltage to bring the signal on-scale. Instead, simply re-stain the beads with less antibody. Often times, staining the beads with 1/2 to 1/10 the concentration used on the cells will keep the signal on-scale, while keeping the signal above that of the cells that the compensation is to be applied to.
Step 2: Collect the data and make sure there is a sufficient number of events.
After staining the carrier, it’s time to collect the compensation controls. Since compensation is a statistical calculation, the more data collected, the more accurate the compensation will be.
As shown in this data below, as the number of collected events increases, the compensation values move towards the actual compensation value.
For bead-based compensation, it’s recommended to collect at least 10,000 events. For cells, it’s recommended to collect at least 30,000 events.
Step 3. Calculate compensation correctly.
As shown in Tung et al., (2004), how compensation is calculated is based on the matrix algebra.
For the above matrix to be calculated correctly, there needs to be a positive and a negative population in each sample. Since the autofluorescence of the positive and negative carrier need to be matched, you should NOT rely on a universal negative.
All major software compensation packages allow for the use of a single control for the negative population, but again, this should be avoided. In the figure below, unstained beads are shown in red, while unstained cells are shown in blue. As the figure shows, if the experiment is being compensated with beads, and a universal negative of unstained cells is being used, compensation will be incorrectly calculated (note the excess of ‘Primary Signal’).
However, if unstained beads are used in each sample, the resulting compensation values will be correct. As such, make sure ALL of your samples contain a positive and negative fraction in them. You should also make sure that you gate around each positive and negative fraction to define each compensation control for each specific fluorochrome.
Step 4. Apply the compensation values and inspect the results.
Once your compensation values have been calculated, it’s time to apply them to your data. At this point in the compensation process, it’s important to inspect your results. For example, the below figure displays data that has been properly compensated using beads.
As you can see above, the data is compensated but the display is troublesome. The reason the data is displayed incoherently is because it has yet to be transformed.
Transformation allows the full spread of the data to be visualized, while removing events off the axis. As shown below, when the correct transformation is applied, the data around ‘zero’ on both the Y-axis and X-axis is re-plotted. Now the data is shown WITHOUT being compressed against these axes.
Automatic compensation is a flow cytometry best practice. When compensating a 4-color experiment make sure you choose the correct carrier for compensation, collect the data and make sure there is a sufficient number of events, calculate compensation correctly, and apply the compensation values and inspect the results. Failure to properly compensate the data will result in erroneous conclusions which may kill an otherwise promising project. For those who must manually compensate due to their instrument, it’s best to under-compensate the data and controls and then bring them into a third party software to finalize the compensation using the software’s automatic compensation protocols.
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My other passions include grilling, wine tasting, and real food. To be honest, my biggest passion is flow cytometry, which is something that Carol and I share. My personal mission is to make flow cytometry education accessible, relevant, and fun. I’ve had a long history in the field starting all the way back in graduate school.
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