Herein we discuss spectral flow cytometry panel evaluation including the pilot experiment, data acquisition, and data evaluation. 

Explore spectral flow cytometry reagents  Spectral flow cytometry experimental setup

Pilot experiment

Now that you have determined the theoretical panel design, purchased and titrated the antibody conjugates and viability stain, as well as defined the protocols and controls (biological and technical) it is important that you run a pilot experiment (Figure 1). This will allow you to refine the protocol steps, reagent selection, and identify any inherent technical or biological variability for the antigens of interest. The pilot experiment may also highlight issues related to the resolution of populations of interest and may dictate if the panel needs to be redesigned [1]. Remember, panel design is often an iterative process—designing, validating, and analyzing high-dimensional spectral flow cytometry panels takes significantly more time than running the final experiment.

Figure 1.Flow cytometry experimental process overview.

Data acquisition

Run the initial data acquisition for all controls and full sample using the settings recommended in your instrument guidelines, prior experiments, or peer-reviewed publications. Please note that if you are running a spectral sorting experiment, it is recommended that you first evaluate data collected from all controls (unstained cells and single stain cells) prior to sorting the cells.

Data evaluation

In this section, we provide you with basic guidelines on how to approach the evaluation of your data and include a few examples of the types of issues you may encounter. It is by no means exhaustive in its nature.


The first run should be to determine if there is any autofluorescence in the unstained sample when compared to the single stained controls or the fully stained sample. It is also important to note that some samples may not have identical autofluorescence signatures, especially with heterogeneous cell types. An example of a heterogeneous sample is lysed whole blood that contains monocytes, granulocytes, and lymphocytes. Consult the instrument guidelines for specific procedures to run these analyses.

Once you have confirmed that autofluorescence is not a factor, it is time to apply unmixing to all the remaining controls and sample. Multi-parameter data generated by a spectral flow cytometer relies on the use of unmixing algorithms to determine the contribution of each fluorophore (Figure 2) to the total collected emission signal [2; also see Spectral Flow Cytometry Fundamentals]. The algorithms calculate the fluorophore combinations and their intensities making up the emission profile of each cell.


Figure 2. Example of autofluorescence extraction. PrimeFlow RNA detection was used to label mRNA in human U937 cells. Cells were treated with PrimeFlow RNA detection kit and were either unstained or stained before detection on the Cytek Aurora(TM) spectral flow cytometer 3-laser system. (Panel A). Unstained cells were mixed with stained cells and analyzed before and after autofluorescence removal (Panel B).


It is important to exclude cellular aggregates and dead/dying cells to ensure they do not increase background or create false positive events that could obscure true positive signal detection. See data on the Spectral Flow Cytometry Panel Controls and Sample Preparation page that demonstrates the impact of including dead cells within spectral samples and describes reagents that be used to accomplish the removal of dead cells from the analyses.

Ensure enough gated events have been collected for single stain controls, in some instances this number may need to be increased (i.e., rare cellular targets). Additionally, you can confirm how many cells will need to be acquired to collect enough target cells for a statistical comparison (detect an effect if there is one to be measured). The more events captured the lower the chance of making a false negative statistical error, which is important for data analysis and ultimately interpretation. It is important to note that if this is not possible due to the rarity of a population, it may only be possible to provide a descriptive interpretation.

Single stain controls

Initial visual evaluation can be done by viewing each single stain control in a two-parameter plot versus all fluorophores. After unmixing, the single stain controls should have equal medians for the positive and negative populations, while populations with unmatched median values or distorted negative populations reveal issues to investigate. Figure 3 shows an example where single-stained cell controls are plotted using the same marker for the x-axis of all plots and a different fluorophore on each y-axis. In Figure 3A, you see that there is no contribution from Fluorophore A or Fluorophore B to either positive or negative Fluorophore X populations. Figure 3B, on the other hand, shows contributions from Fluorophore C and D to both positive and negative Fluorophore X populations, indicating a need to explore these samples further.

Figure 3. Evaluation of results using single stained cell controls. Reviewing all plot combinations of the single stained cells where the same marker is placed on the x-axis and plots with the y-axis represent all the other fluorophores in the panel. This allows for visual inspection to confirm expected unmixing results or reveal problems to investigate. In this example, Fluorophore X is evaluated against four other fluorophores. (A) Visual inspection confirms expected unmixing of Fluorophore X with Fluorophore A and Fluorophore B, as the medians of the positive and negative populations match (black lines). (B) Visual inspection reveals issues of Fluorophore X with Fluorophore C and Fluorophore D, as the medians of the positive and negative populations do not match (red lines), indicating troubleshooting is needed.

Additional evaluation steps for the single stained sample controls include comparison of the staining pattern of the conjugated antibody to the fully stained experimental sample. By overlaying the staining patterns, any loss in resolution can be identified (Figure 4). Resolution losses, seen as either a broader negative population or a dimmer positive population, are frequently attributed to non-optimal fluorophore selection, non-optimal titer, or sample preparation issues.

Figure 4. Signal resolution evaluation. Comparing single stained cells with fully stained cells is one method that can be used to evaluate signal resolution. This representation shows human lymphocytes gated to show overlay histogram plots of a single stained cell sample (purple line) and cells labeled with the full panel (blue line), to determine if resolution was maintained in the full panel.


Full stained sample

A visual inspection of all combinations of plots in the full experiment to evaluate population resolution can be useful with attention to combinations using highly similar fluorophores. A visual confirmation of expected patterns can be performed, as well.

At this point, any issues that arise with the unmixed fully stained sample can still be caused by issues with the single stained controls. To help isolate the cause use these steps to determine if the same issue is found in both the single stained controls and the full stained sample.

  • Examine all the single stained controls to ensure there is no contamination of any other control sample. If there is contamination the control will need to be replaced.
  • If the issue is only found in the fully stained sample, you might try changing instrument settings. Before changing the settings consult the instrument guidelines.
  • If using antibody-capture beads for single stain controls, compare the spectra obtained with cells and with beads to see if the spectral signatures are identical.
  • Other situations that may need adjustment include using a single stained cellular control with a low-abundance antigen, using a fluorophore with a low staining index, or a fluorophore that emits into an area of high spectral spillover.

FMO controls

Fluorophores affecting resolution can be singled out by building partial panels or using FMO or Fluorescence Minus x (FMx) controls. When swapping out incompatible fluorophores, new additions should be assessed regarding their similarity index values, brightness, and spread matrix values.

It can also be useful to compare the Fluorescence Minus One (FMO) sample to the fully stained sample. The FMO sample can be used as a quality control to visually confirm a low-expression population, and to evaluate spreading on population resolution. See the Spectral Flow Cytometry Panel Controls and Sample Preparation page for more information.

Additional thoughts around data evaluation

There are a few additional items to consider when evaluating your panel.

  • Higher spread is expected when fluorophores with very similar spectral signatures are used together and should be reserved for use with antibodies detecting mutually exclusive populations to minimize the effect on resolution—see the Flow Cytometry Experiment Process—Spectral versus Conventional page for more information. Fluorophores with poor resolution, due to spreading, may be replaced with brighter ones, if available, to improve population separation. Selecting dimmer fluorophores on highly expressed antigens can also help mitigate spreading. To learn more, see the Spectral Flow Cytometry Panel Design page.
  • If resolution losses are observed when all the reagents are combined in the experimental sample, the sample preparation protocols should be reviewed. Improvements may be seen when different antibody titers are chosen, when staining steps are reordered, or when the timing of reagent additions is modified.
  • Antibodies combined in a cocktail, to save processing time, may result in unwanted interactions that distort staining results. Antibody cocktails should be tested to determine if they impair resolution.
  • If issues are revealed after unmixing, action should be taken to determine root cause. To reach optimal population identification the panel may need to go through multiple rounds of optimization. The panel may require rework by modifying the controls used, adjusting reagent selection, modifying reagent titer used, or fine-tuning sample preparation, or staining protocols.


In summary

When any issues revealed during the evaluation phase have been addressed and revisions are no longer necessary, the panel is considered optimal for the detection of the cellular populations of interest. Initial assessment of the basic cellular properties of the sample acquired can now be performed. Using traditional flow cytometry gating techniques, populations of interest are included while debris and cellular aggregates are excluded. Using a viability dye, dead/dying cells are identified and excluded from analysis. Acquisition stability is evaluated using the time parameter, by displaying either scatter or fluorescent signals in a dual parameter plot vs. time, and if necessary questionable events can be gated out. Once the data identify live single cells, the remainder of the analysis can be performed using hierarchical gating or can be carried out with the aid of advanced computational tools.

Next steps
References and suggested reading
Style Sheet for Global Design System

For Research Use Only. Not for use in diagnostic procedures.