Here is a compilation of all the key terms for spectral flow cytometry. Browse the list below to find the definitions to terms that interest you.

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Spectral flow cytometry fundamentals 

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Antibody capture bead 

a microparticle coated with immunoglobulins that react with species-specific fluorophore-conjugated antibodies. This type of particle is used to generate single stain controls to calculate compensation or to unmix data.

To help ensure accuracy of the calculations, an antibody-fluorophore captured by a specific antibody capture bead can be compared to cells labeled with the same antibody-fluorophore to check that the spectral signature is the same as when bound to cells.

Antibody cocktail mixture a preparation of individual fluorophore-conjugated antibodies that are pooled into a single sample for ease of use, to reduce pipetting steps and error, and to save time when staining cells.
Antigen classification 

the tier ranking of antigens based on their density and expression patterns.

Primary antigens are those that are well characterized and identify broad subsets of cells. Although secondary antigens are well characterized and have higher antigen density, they may represent a continuous expression pattern instead of discrete positive and negative populations. Tertiary antigens are either expressed at low levels or are uncharacterized. Classifying antigens is an important step in panel design and precedes the pairing of antibodies with fluorophores.

Antigen density 

the number of target molecules or receptors expressed on or in a cell.

Understanding the antigen density is important in panel design in order to pair antigen density with fluorophores of appropriate brightness level. Cells with high antigen density are best paired with dim-moderate fluorophores, while cells with low or undetermined antigen density are best paired with bright fluorophores.


Backbone panel 

a base or core optimized multiparameter panel used to identify common cell types, with flexibility to add in additional antibody-conjugates later (“drop in”) for deeper immunophenotyping.

Using an optimized backbone panel is a way to save time on panel design by using pre-defined antibodies with pre-determined fluorophores.


Cellular autofluorescence 

the intrinsic fluorescence of cells caused by the presence of molecules such as NADPH, riboflavin, collagen, elastin, aromatic amino acids, and cellular organelles (i.e., mitochondria and lysosomes).

In flow cytometry, cellular autofluorescence can affect sensitivity by increasing background and interfering with detection of dim fluorescent signals. The level of autofluorescence can be determined by collecting data on unstained cells of the same type used in the experiment. It may be necessary to have multiple samples for autofluorescence controls; for example, when using resting and stimulated lymphocytes in the same experiment.

Different cell types can have different inherent levels of autofluorescence and may change as cells are treated or as cells age. In general, larger, more granular cells have higher autofluorescence because of the increase in the number of autofluorescent compounds. Most autofluorescence is detected at shorter wavelengths of light, absorbing in the 350–500 nm range and emitting around 350–500 nm. There is less autofluorescence at longer wavelengths, and detection of emissions above 600 nm will have less interference from autofluorescence. Spectral flow cytometry can identify and remove autofluorescence to improve resolution.

Cluster analysis a statistical method for processing data by organizing items into groups, or clusters, based on how closely associated they are. Cluster analysis is an unsupervised learning algorithm, meaning that the number of clusters that exist in the data is unknown before running the model. Unlike other statistical methods, cluster analysis is typically used when there is no assumption made about likely relationships within the data.

the simultaneous expression of two or more antigens on or in a cell.

Antigens that are co-expressed are best paired with fluorophores that have low degrees of similarity in multiparameter panel design, so there is less impact on data spread.

Compensation a mathematical correction that aims at removing fluorescence spillover of a given fluorophore from secondary detectors. It is a necessary to calculate compensation when two or more fluorophores are used in a panel.
Complexity index/measurement 

a metric used to assess the level of uniqueness of all the fluorophores present in a panel.

The complexity measurement is useful for evaluating fluorophore combinations during panel design. A lower complexity value indicates high probability that the combination of fluorophores will yield high-resolution data with reduced spreading-error. A higher complexity value will indicate fluorophore combinations that give rise to spreading-error yielding data that may result in poor resolution.


Dimensionality-reduction the reduction of data with multiple parameters to a few dimensions for improved data visualization and interpretation. A type of unsupervised learning technique to visualize all points in lower-dimensional space.

a process where a smaller number of events is used as representative of the whole sample. The data is randomly sampled in order to reduce computation time.

Advanced analysis tools commonly used with large, complex data sets may benefit from using this process to visualize information to facilitate analysis of the data set.

Dump channel 

also called an exclusion gate is the intentional exclusion of events from analysis that are positive for a target or target combination, including viability staining. A dump channel combines multiple antibodies sharing the same or similar fluorophores, to group and exclude anything that is not of interest.

In spectral flow cytometry, the number of fluorophores that are possible is less limiting than conventional flow cytometry, making the use of a dump channel unnecessary. If used in spectral flow cytometry, the fluorophores in the dump channel must be identical to be correctly unmixed. Avoid combining a viability dye with similar but non-identical spectral signatures to the fluorophore used in the dump channel, as this will result in unmixing errors. Also, avoid using tandem dyes in a dump channel, even tandem dyes of the same donor and acceptor. Lot-to-lot variability and exposure to light over time can cause spectral emission variations.


FlowSOM an unsupervised learning technique for clustering and dimensionality-reduction to analyze flow cytometry data using a Self-Organizing Map to identify cellular subsets and visualize relationships.
Fluorescence Minus One (FMO) a sample of cells stained with all the fluorescent reagents used in a multiparameter panel except one. A multiparameter panel will have one FMO control for each fluorophore used.
FMO controls 

these are used to determine the cut-off point between background signal and positive populations.

FMO controls are more accurate gating controls than unstained cells or single-stained samples because they consider the widening of the negative population due to spreading-error contributed by all the other fluorophores used in the experiment.

Fluorescence Minus X (FMx) a sample of cells stained with the fluorescent reagents used in a multiparameter panel except for a few (x). This type of partial panel helps investigate the impact certain additions or combinations of reagents may have on background, spread, and population resolution.
Fluorescence a type of luminescence occurring when certain substances emit light energy after absorbing light or other electromagnetic radiation. Molecules reach an excited state after absorbing light energy and as they return to their ground state, emit light of longer wavelengths.
Förster or Fluorescence Resonance Energy Transfer (FRET) the process by which energy is transferred between two nearby fluorescent molecules. A donor chromophore in its excited state may transfer energy to an acceptor chromophore. The efficiency of transfer is inversely proportional to the distance between donor and acceptor, making FRET sensitive to small changes in distance.


Mean or Median Fluorescence Intensity (MFI) 

a statistical measure of the fluorescent mid-point (central tendency) of a population (distribution). It is often used to relate the level of expression of a protein.

To control for technical variability (reagent and instrument) and enable the comparison of samples analyzed over an extended period, multi-peak fluorospheres can be acquired alongside a cell sample to normalize MFIs. Median is considered a more robust statistic than the mean, as it is less influenced by outliers or skew. When using this measure, it is recommended to list out which value (mean or median) is being used for clarity.

Mutually exclusive 

when two antigens are not expressed simultaneously on or in a cell.

Antigens that are mutually exclusive may be paired with fluorophores that have higher degrees of similarity in multicolor panel design with less impact on spreading error.


Normalization a preprocessing step performed on a set of data to minimize the effects on measurements derived from technical variation rather than biological differences (i.e., equipment setup, acquisition settings, sample preparation).


Panel builder online tool that guides selection of fluorescent antibody conjugates for a conventional or spectral flow cytometry panel by providing a customizable experience.
  Like spectral viewers, a panel builder tool will display the excitation and emission spectra for fluorescent dyes and proteins. It shows available antibody conjugates to facilitate selection of appropriate antibodies for a multiparameter experiment using a specific instrument configuration. For guiding spectral panel design, similarity and complexity measurements are also included.
Primary antigens well characterized antigens that identify major subsets of cells. Also referred to as lineage markers.
Principle Component Analysis (PCA) an established dimensionality-reduction method for reducing multiple parameters to a few dimensions which can be more readily visualized and interpreted. PCA uses unsupervised linear learning algorithms.


Saturating titer 

the antibody concentration where additional antibody does not increase the signal intensity.

Secondary antigens often well-characterized antigens that may have high antigen density but may also have a continuous or broad expression pattern.
Separation index 

a metric for evaluating the relationship between positive and negative fluorescent populations.

The separation index is calculated from the difference in the median fluorescence intensity (MFI) between positive and negative populations, taking the spread of the negative into account. The right-hand slope of the negative is weighed more heavily, to minimize error of the negative fluorescence distribution.


A higher separation index value represents greater separation between positive and negative populations. The separation index is useful for measuring and comparing the relative brightness of various fluorophores on a given instrument and determining the optimal antibody concentration for use.

Similarity index/measurement 

a comparison metric used to assess the uniqueness of a pair of fluorophores. A higher value means the spectral signatures of the two fluorophores are similar, while a lower value means the spectral signatures of the two fluorophores are different. The similarity measurement is dependent on the specific instrument configuration used.

It is recommended avoiding the use of fluorophores with similarity indices greater than 98 to limit excessive data spreading. High similarity values, between 90-98, may correlate with high spread and should be used with caution, especially if the antigens are co-expressed. When choosing fluorophores for antigens that are co-expressed, we recommend avoiding those that have similarity measurements greater than 70.

Single stain control 

a sample containing cells or antibody capture beads labeled with only one fluorophore-conjugated antibody or fluorescent compound used in a panel. These controls are used to calculate compensation or unmix data.

The positive and negative populations require identical autofluorescence properties, and the positive population should be as bright as or brighter than the experimental sample. Importantly, for spectral flow cytometry, single stain controls should share the exact same spectral signature and be processed in the exact same manner as the experimental sample.

Spectral signature fluorescent emission of a fluorophore collected from all the instrument lasers and fluorescence detectors combined.
Spectral viewer 

online tool displaying the absorption and emission curves of fluorophores.

  This tool is useful in learning about fluorescent dyes and proteins and facilitate selection of appropriate dyes when designing a multiparameter experiment. Many spectral viewers allow inclusion of standard instrument-specific configurations to help compare fluorophores to determine their uniqueness and compatibility when used in a panel.
Spectrum a range of emission wavelengths.
Spillover the fluorescent signal of a given fluorophore detected by secondary detectors instead of its primary detector. Spillover is accounted for and corrected when the data is compensated or unmixed.
Spread (spreading error) 

a photon-counting error revealed post-compensation or post-unmixing. High spreading will result in reduced signal resolution.

To minimize spreading error, use fluorophores with unique spectral signatures. Using fluorophores with high similarities will introduce spreading error and thus, should not be used for targets that are co-expressed. Spreading error is also a function of fluorescence intensity. Using fluorophores that contribute most to the spread are best used with low expression targets.

Spread matrix a grid displaying the spillover-spreading error values for every fluorophore pair used in a panel. It quantifies how much spread a given fluorophore gives or receives to help guide panel design.
Stain index a metric for evaluating the relationship between positive and negative fluorescent populations. The stain index is calculated from the difference in the median fluorescence intensity (MFI) between positive and negative populations, taking the spread of the negative into account.

A higher stain index value represents greater separation between positive and negative populations. The stain index is useful to measure and compare relative brightness of various fluorophores on a given instrument and to determine the optimal antibody concentration for use.

Supervised learning methods require training data which creates a model to learn mapping from input to output. These data sets are designed to train or supervise algorithms into classifying data or predicting outcomes.


Tandem dye 

a dye composed of two covalently bound fluorescent molecules in close proximity, a donor, and an acceptor molecule. Light energy excites the donor molecule and the energy from the donor molecule is transferred to the acceptor molecule through a process known as Förster (or Fluorescence) Resonance Energy Transfer (FRET).

The tandem dye behaves as one fluorophore with the excitation properties of the donor and the emission properties of the acceptor. Tandem dyes were created to produce fluorophores with longer Stokes Shift and can be used with single-wavelength excitation sources commonly used in flow cytometry. Tandem dyes are susceptible to light exposure, and their manufacturing process yields variability between lots; therefore, their spectral signature should be verified with every use.

t-Distributed Stochastic Neighbor Embedding (t-SNE) a commonly used non-linear dimensionality-reduction algorithm for single-cell biology, used to visualize and interpret high-dimensional single-cell data.
Tertiary antigens antigens that are either expressed at low levels or are uncharacterized.

a process carried out to identify the optimal antibody concentration to use for a specific cell type and a given application.

Titration involves staining a cellular sample with a series of dilutions to determine the concentration that provides the best separation between positive and negative signal. It is recommended that all fluorescent reagents be titered to find the optimal amount for use.


Uniform Manifold Approximation and Projection (UMAP) a commonly used non-linear dimensionality-reduction technique for single-cell biology, used to visualize and interpret high-dimensional single-cell data. Similar to t-SNE, but with faster processing speeds and improved visualization.

a mathematical method used to distinguish the fluorescent contributions of multiple fluorophores in a multiparameter sample. Unmixing calculations commonly rely on statistical methods such as ordinary least squares and weighted least squares.

Algorithms can treat the spectral signature of an unstained sample as a separate contribution, similar to one of the fluorescent parameters, to extract autofluorescence and improve signal resolution. Unmixing relies on robust single stain controls that identically match the spectral signatures present in the experimental sample.

Unsupervised learning methods take a set of data that contains only outputs to find structures in the data, via grouping or clustering. These represent most of the development for analysis of high-dimensional flow cytometry data sets.


Viability dye 

a fluorescent dye used to discriminate live cells from dead cells, such as an impermeant nucleic acid-binding dye, amine-reactive dye, or enzymatic dye.

Dead cells in flow cytometry are defined as cells having a compromised outer membrane. Dead cells can be identified and gated out so only viable cells are used for data analysis.

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