How to Translate Flow Cytometry Plots: Gates, Signals and Percentages

How to translate flow cytometry plots easily begins with a basic distinction: a dot plot is not a photograph of cells, and a gated percentage does not automatically describe the entire original sample. Flow cytometry charts encode instrument measurements, populations selected by analysis rules and labels assigned to those populations. A good translation into clear prose must retain all three layers.

People searching for “how to read a flow cytometry dot plot,” “flow cytometry gating explained,” or “how to interpret quadrant percentages” are often trying to understand why one scatterplot contains several clusters, percentages and colored boundaries. The difficult part is rarely the vocabulary alone. It is keeping track of which events were measured, which events were excluded, which gate serves as the denominator and what a fluorescence marker actually means in the experiment.

This guide explains how to translate flow cytometry histograms, two-parameter plots and gating diagrams into accessible written language without changing the scientific claim. It covers axes, event density, forward and side scatter, single-cell selection, compensation, control samples, population percentages and the uncertainty around biological labels. The approach is suitable for educators, scientists communicating across languages, scientific editors and accessibility writers. It is educational and does not interpret patient-specific diagnostic findings.

A flow cytometry plot is a measurement summary

Flow cytometry instruments measure characteristics of particles or cells passing through a detection system. Depending on the instrument and protocol, they can record scattered light and fluorescence at multiple channels. The software then displays recorded events as dots, density patterns or histograms. A plot is therefore a selected view of a multivariable dataset, not an image showing each cell’s physical appearance.

A dot may represent one event, although display settings can aggregate or subsample observations. A colored region may represent density rather than a biochemical color possessed by the cells. A polygon or oval usually indicates a gate used during analysis. The translator’s first job is to identify which marks belong to the measurement, which to the display style and which to the analyst’s decisions. Mixing them turns a scientific diagram into an inaccurate story about what the cells supposedly look like.

The axes reveal which properties are compared

A two-dimensional flow cytometry plot places one measurement on each axis. The left-right position might encode forward scatter, one fluorescence channel or another transformed quantity; the bottom-top position might encode side scatter or a second fluorescence channel. These labels are not interchangeable. Without them, it is impossible to know what a cluster’s location means.

Transcribe the axis names before describing the distribution. Retain detector or marker labels exactly, including plus and minus signs where applicable. Check whether the scale is linear, logarithmic, biexponential or another transformation. “A population lies toward higher fluorescence on the x-axis” is safer than “cells are bigger” unless the axis actually supports that interpretation. A diagram’s geometry is meaningful only after the quantities on its axes are identified.

Forward scatter and side scatter have different roles

Forward scatter, often abbreviated FSC, is associated with optical characteristics related to particle size under specified instrument conditions. Side scatter, often abbreviated SSC, is related to light scattering and can reflect aspects of internal complexity or granularity. These are useful approximations for familiar gating strategies, but neither is a simple ruler that directly reports cell diameter or a universal measure of health.

A translator should not turn “higher SSC” into “larger cells” or “higher FSC” into “more granular cells.” Those shortcuts may be attractive because they use ordinary adjectives, yet they swap the physical relationships being represented. Instead, describe changes in scatter signal and attribute any biological interpretation to the experimental context. A plot without properly identified instrument channels should not be rewritten as a confident cell-type classification.

Events, cells and particles are not always synonyms

A recorded event is what the instrument registers. A cell is a biological entity that may produce an event, but debris, aggregates and other particles can also enter the dataset. One event can sometimes arise from more than one cell passing together. A raw event count is therefore not necessarily an exact count of individual viable cells, even when the experiment was designed to measure cells.

Respect the terminology used in the figure. If a caption says 20,000 events were acquired, do not rewrite that as exactly 20,000 living cells. If a subsequent gating step identifies a single-cell population, describe that step separately. Scientific accuracy here depends on preserving the path from raw detector records to a selected subset. The distinction matters even when the final plot looks like a simple scatter diagram.

A gate is an analytical selection, not a membrane around cells

A gate is a defined region or rule used to select events for subsequent analysis. It might be drawn as a polygon, rectangle, ellipse or threshold. Its boundary reflects the analyst’s strategy and controls, not a literal physical wall separating two biological groups. Different valid gating approaches can produce different selected populations from the same underlying file.

When converting a plot to text, name the gate, the coordinates or criteria it uses and the population that follows from it. If a plot labels “P1,” retain P1 until you know what the experiment defines as P1. Calling it “healthy cells” or “target cells” without documentary support invents meaning. Translate the analyst’s label faithfully and explain its role after verification. Boundaries in a graph are decisions about data inclusion.

Gating hierarchy changes the denominator

One flow cytometry figure often contains a sequence of plots: first events are selected from a scatter region, then singlets are chosen, then viable events may be retained, and finally fluorescence markers define subsets. Each plot may show a percentage relative to its parent gate. A downstream “40%” does not necessarily mean 40% of all acquired events.

Imagine 10,000 acquired events, of which 8,000 pass an initial gate, 7,000 pass a singlet filter and 5,000 pass a viability gate. If a marked population contains 2,000 of the 5,000 viable selected events, it represents 40% of that parent population but 20% of all acquired events. Translating one value as the other doubles the reported fraction. That is why the gate hierarchy and denominator should appear in the prose whenever percentages are reported.

How to describe a standard gating sequence

A typical educational workflow may first examine FSC versus SSC to select a relevant population, then use paired measurements to exclude doublets, then use a viability indicator or fluorescence controls before defining a marker-positive subset. This is an example, not a universal standard that applies to every experiment. Certain designs omit steps, reverse their order or use different measurements.

Translate the actual chain shown, not a remembered textbook sequence. A good sentence might read, “Events within gate P1 were passed to the singlet selection; the retained events were then analyzed for two fluorescence markers.” If the caption explicitly defines P1 as a cell-enriched scatter region, include that explanation. Otherwise keep the code. A reliable textual account lets readers trace a reported percentage back through each gate.

Singlets and doublets require separate language

Two cells passing together may produce signals that differ from single-cell events. Analysts often use pulse-related measurements such as area, height or width to enrich for singlets. These parameters depend on instrument configuration. A plot might compare FSC-A with FSC-H, or use another suitable pair of features. Do not translate “singlet gate” into “all living cells” or “single molecule.”

State what the analysis selected, such as “events consistent with single particles under the reported pulse-geometry criteria.” Avoid assuming that every event outside the gate is a damaged cell. The original scientific figure may treat exclusion as quality control rather than diagnosis of cell condition. This separation is essential when the article will be read by people outside the specialty who might attach everyday meanings to terms such as single, double or viable.

Viability gating does not prove clinical health

Some experiments use dyes or other indicators to distinguish events associated with intact versus compromised membranes under defined conditions. A so-called live/dead gate can support a laboratory classification of a measured cell population. It does not tell a reader whether the source organism or a person is healthy. That leap crosses multiple levels of inference.

Use the method’s own stated criterion, and avoid adding medical implications. “Events excluded by the viability-dye gate” is clear without pretending to establish a broad diagnosis. If the source indicates a particular staining strategy and threshold, retain it. If the control is not described, do not assume which side of the plot should be treated as viable. Color and intensity assignments depend on the reagent and analysis design.

Fluorescence channels are instrument readouts

Fluorescence signal comes from labels or properties measured in specified detector channels. A label such as FITC-A, PE-A or a marker name paired with a fluorophore communicates instrument and reagent information. Some figures place a biological marker name directly on the axis instead of the detector channel. The translator should preserve both where supplied, rather than substituting one for the other carelessly.

An increase in signal does not automatically mean that a cell contains a proportionally larger amount of a protein. Background, labeling, instrument response and signal transformations affect the measurement. A careful caption says “higher signal in the specified fluorescence channel” before interpreting marker expression. If the experiment validates a marker-positive threshold, that is a second, explicitly defined analytical statement.

A marker name is not automatically a cell identity

A population labeled with a surface marker may be enriched for a particular type of cell, but many cell types share markers and marker expression can vary with conditions. One fluorescence-positive gate rarely proves a complete biological identity in isolation. Scientific reports often combine several markers and controls to support an identification.

Translate the stated phenotype and the authors’ supported label rather than treating an individual marker as definitive. If a plot says “CD4-positive events” and a paper separately defines a cell subset using other criteria, preserve those components. The term positive here means meeting a laboratory fluorescence or gating criterion, not moral approval or a clinical test verdict. Explaining the local meaning of a word can prevent a strikingly large misunderstanding.

Quadrant plots: four labels, four different relationships

Two-marker dot plots sometimes use vertical and horizontal thresholds to divide events into four regions. The quadrants can correspond to low/low, high/low, low/high and high/high relative to the chosen thresholds. Their position on screen depends on the actual axes; the same upper-right quadrant may mean something different after the markers are swapped.

Translate by axis names before using quadrant numbering. Say “events above the threshold for both displayed markers” rather than “double-positive” if the threshold’s meaning is not clear. If the source uses a validated marker-positive convention, include “double-positive” with the axis names so the description survives changes in page orientation. Never assume Q1 always means the upper-left region across all software packages.

Percentages in quadrants must retain their population base

A quadrant might display 12.4% in the upper-right region. Before writing “12.4% of the sample,” determine whether it refers to all recorded events, the current parent gate or only a subset displayed after exclusions. If the plot follows three gating steps, the denominator is often not the raw acquisition total. The caption may already say “percent of parent” or “percent of total.”

In translated text, make that denominator explicit whenever it is recoverable: “Within the displayed viable singlet gate, 12.4% of events lie in the upper-right quadrant.” If the source does not reveal the denominator, avoid filling it in from habit. Readers can draw very different biological conclusions from the same percentage if its base population changes. This is a mathematical translation problem as much as a vocabulary problem.

Dot density and color need a legend

A dense cluster of dots may look darker, or software may display high-density regions in bright colors. Neither appearance is necessarily a direct measure of fluorescence. A density map can use an arbitrary color scale to encode event concentration in the display. If that color key is omitted, an accessible description should avoid treating red or blue as a molecular property.

Read the legend. Identify whether colors encode event density, a sample group, a manual gate or fluorescence itself. If the plot combines overlaid populations from different treatments, distinguish the overlays from the two plotted measurement axes. “Red points represent treated events” is different from “red indicates stronger fluorescence.” The graphic’s chosen colors matter only through their documented mapping to data.

Histograms describe distributions along one measurement

A flow cytometry histogram may plot event count, frequency or normalized distribution against signal intensity for one channel. Its peak describes where a concentration of events appears on that axis, not necessarily a new chemical substance. Overlaid histograms often compare samples, stains or conditions. Their meaning depends on normalization and how many events contributed to each curve.

Translate x-axis and y-axis separately. “The treated population’s fluorescence distribution shifts toward higher intensity” can be appropriate when the axes and overlays justify it. “The treatment produced more cells” is not implied by a rightward shift in a normalized histogram. If the plot is offset or normalized to its own peak, raw event counts cannot be compared from curve height alone. An accurate caption protects that distinction.

Geometric mean, median and percent-positive are different summaries

A flow cytometry report may summarize fluorescence using median fluorescence intensity, a geometric mean or the fraction exceeding a threshold. These are not synonyms, and the result can differ depending on the summary chosen. The exact abbreviation MFI is especially ambiguous in some contexts: authors may use it for median or mean fluorescence intensity.

Translate the full metric defined in the source document. If it says “median,” preserve median; if it says “geometric mean,” preserve that term. When the original uses MFI without clarification, do not invent the expansion. A note such as “MFI is not defined in the source caption” is safer than silently choosing one interpretation. Many apparent disagreements between studies are actually disagreements in measurement definitions or denominators.

Logarithmic and biexponential scales change visual spacing

Fluorescence data often span large ranges, so software may use nonlinear transformations to display them. Equal distances along such an axis do not necessarily correspond to equal arithmetic changes in raw signal. A cluster appearing twice as far to the right should not be described as having twice the fluorescence. Near-zero and compensated negative values may also be displayed in special ways.

Keep axis transformation information when it is provided. If a source uses a log scale, say “on the logarithmic fluorescence axis” where that affects interpretation. Avoid invented fold changes derived from visual distances. This is another example of why interpreting the axis precedes interpreting the pattern. A graph’s geometry is a designed representation of measurements, not the measurements themselves.

Compensation and spectral unmixing are analytical operations

Fluorescent signals can spill into detectors other than their intended channels. Compensation or, in appropriate systems, spectral unmixing helps separate contributions across detectors using controls and models. These are technical corrections, not cosmetic color adjustments. A plot may look very different before and after them, and negative transformed values can appear without indicating a physically negative amount of fluorescence.

Translate the processing status if it appears in the source: compensated, uncompensated, unmixed or otherwise processed. Do not call a value “impossible” merely because the displayed scale includes a negative transformed region. Conversely, do not guarantee that a corrected plot is free from all overlap or error. Good scientific language reports what processing was applied and preserves any limitation noted by the analyst.

Single-stain controls and unstained controls matter

Controls help determine signal background, detector response and separation among fluorescence channels. An unstained control can help describe baseline behavior, while single-stain controls play roles in compensation or unmixing workflows. Other controls may address specificity, viability or threshold placement. Not every experiment uses the same set.

In translation, preserve each control’s purpose and relationship to the plotted data. The name “negative control” alone may not explain which property should be absent. A better description says what the control lacks or what it was designed to test, when that information is supplied. If a figure compares samples without showing the relevant control, do not invent one. The reader deserves to know which thresholds are documented and which remain unexplained.

Fluorescence-minus-one controls do not mean no fluorescence

A fluorescence-minus-one, or FMO, control omits one fluorescence component while retaining the others relevant to a panel. It can help establish boundaries in multicolor experiments, particularly where spillover and background complicate a marker’s positive threshold. The phrase can be misunderstood by beginners as meaning a completely unstained or non-fluorescent sample.

Translate the acronym with its definition and the marker omitted. Distinguish FMO from an unstained control and from an isotype control, which serves a different and context-dependent purpose. A gate based on an FMO distribution should not be described as chosen arbitrarily if the figure documents the control. Preserving the reason for a gate makes the plotted percentage more interpretable and the analysis easier to verify.

Overlays compare distributions under stated conditions

Flow plots can overlay one sample in blue and another in orange. To translate them accurately, identify the plotted variable, which group each color represents, whether curves are normalized and whether data were acquired under comparable conditions. A rightward shift may show higher measured fluorescence, but its interpretation may be affected by batch effects, staining conditions and other factors.

Do not convert a visual overlay into a biological causal claim without supporting experimental design. “The treated sample has a distribution shifted toward higher signal under the displayed conditions” describes the plot. “Treatment causes protein production to double” requires a validated quantitative interpretation and a suitable comparison. Translation should carry the original study’s inference, not strengthen it from an attractive visual difference.

Panel labels and sample codes must remain linked

Large flow cytometry figures may contain panels A through F, each using different axes or gate stages. Sample labels can include patient-neutral research codes, time points, treatment groups, replicate numbers and marker combinations. Switching two panel letters during translation can move a percentage from the control condition to an experimental condition without changing a single digit.

Build a panel map before writing. Record the original label, displayed axes, parent gate, sample code and key conclusion for every panel. If a source image contains a cropped or illegible identifier, mark it as uncertain rather than guessing. When translating multilingual figures, retain technical channel names or standardized marker designations consistently. Translate descriptive wording separately from identifiers used to track records.

The difference between positive, negative and absent

Within a flow cytometry analysis, “marker-positive” commonly means that an event exceeds a defined threshold or occupies a selected region under the gating strategy. “Marker-negative” commonly means that it does not meet that criterion. Neither label necessarily proves the absolute biological absence of a molecule, especially given background, sensitivity and gating decisions.

A translated caption should preserve the operational nature of these terms. “Events below the stated fluorescence threshold” may be more informative for beginners than “cells have no marker.” Where the source uses positive and negative categories, explain that those categories are defined by this analysis. This is especially important for world-facing education: the everyday meanings of positive and negative invite unwarranted medical conclusions.

A hypothetical example with three connected gates

Imagine an experiment with 50,000 acquired events. A first gate keeps 40,000 events within a selected scatter region. A singlet gate retains 36,000 of those. A subsequent fluorescence gate defines 9,000 events in a marker-high region. Within that third stage, the marker-high fraction is 25% of the singlet parent, but it is only 18% of the original acquired event count.

A faithful written description gives the chain: “Of the acquired events, 40,000 passed the scatter gate and 36,000 passed singlet selection. The final marker-high gate included 9,000 events, corresponding to 25% of the singlet population.” If a graph displays only the 25% value, do not replace it with 18% unless you are explicitly performing and labeling a new calculation. The key is to keep the graph’s own denominator visible.

Hypothetical example: two fluorescence markers and four quadrants

Suppose a two-marker plot has Marker X on the horizontal axis and Marker Y on the vertical axis, with thresholds dividing the graph into four quadrants. The upper-right region lies above both thresholds. The lower-right lies above X but below Y. The upper-left lies below X but above Y. The lower-left lies below both. Those relationships are determined by axis position, not by which quadrant number a software package assigns.

For a reader who cannot see the graph, a caption should explicitly describe both markers and the thresholds. A phrase such as “double-positive events occupy the upper-right quadrant” is useful only if “positive” is defined by the analysis. If the image is mirrored or axes are exchanged, the spatial relationships change. A verification pass should therefore match every quadrant description to the printed axes.

Hypothetical example: normalized histograms can mislead

Consider two overlaid fluorescence histograms, each normalized so its own tallest point has the same height. One curve shifts right, and its apparent peak looks similar in height to the other. A careless explanation may conclude that the groups contain equal numbers of events. That does not follow because the curves were independently scaled for visual comparison.

The reliable wording is “The two normalized distributions differ in fluorescence position; the display does not by itself show equal absolute event counts.” If the figure provides counts elsewhere, report those separately. This example is important because graph simplification can remove the denominator from view. Translation must restore the distinction between distribution shape and population size without inventing unreported numbers.

Hypothetical example: a gate cuts through a cluster

A polygonal gate may intersect a dense group of events. A translation that calls everything outside it “background noise” may be unsupported: the excluded events could contain a mixed biological population, overlap or instrument artifacts. The reason for drawing the boundary may be explained in the analysis notes, by controls or by established research criteria.

A suitable description is “The analyst selected the central portion of the cluster using a polygon gate; events outside the boundary were excluded from downstream analysis.” If the source gives a technical rationale, include it. If it does not, acknowledge that the figure alone does not establish why the boundary was placed there. This preserves the ability of a later reader to evaluate the gating decision.

Hypothetical example: control labels disappear in a cropped figure

Imagine a slide displaying two fluorescence quadrants but no legend showing which sample is unstained and which is treated. The source article elsewhere identifies the colors, yet the cropped image does not. A translation based on color stereotypes might assign red to treatment and blue to control. This can reverse the result.

Recover the panel legend from the original source before writing. If it is inaccessible, use neutral descriptors such as “the red-coded overlay” and say that sample identities are not available in the reproduction. Do not infer group identity from which distribution appears brighter. The stronger the perceived result, the more important it is to avoid casual labeling of the plot.

Medical caution: a plotted subset is not a diagnosis

Flow cytometry is used in both research and clinical laboratories, but this guide is about scientific visualization and language, not patient interpretation. Clinical conclusions depend on specialized protocols, instrument quality control, multiple markers, validated gating, reference information and professional judgment. A plot labeled with one marker or a striking percentage is not sufficient for a medical conclusion.

When translating clinical material, preserve the laboratory’s own terminology, measured values, reference ranges and caveats. Do not invent disease labels from a generic cell-subset pattern. If the source uses a diagnostic category, retain the stated category without strengthening it. For patient-specific decisions, qualified professionals must interpret the complete validated record. Communication becomes safer when the limits of a chart are made explicit.

How to write useful alternative text for a dot plot

A short accessible description should state the axes, gate and main distribution. For example: “Flow cytometry dot plot with forward scatter on the horizontal axis and side scatter on the vertical axis. Most displayed events form a dense central cluster. A polygon gate selects the main cluster for further analysis.” This conveys the relationship more effectively than “colorful graph with dots.”

A longer description may add gate labels, shown percentages and source-defined population names. If the figure is one step in a sequence, explain its position: “This is the singlet-selection stage following the initial scatter gate.” Avoid describing every dot or assigning cell identities that the figure does not establish. The goal is to communicate the chart’s reasoning and the analyst’s selection, not its decorative appearance.

How to translate a histogram into ordinary language

Begin with “how many events” versus “how bright a fluorescence signal” only if those are the actual axes. If the vertical scale shows normalized frequency, say that instead of count. Then describe whether a distribution peaks, shifts, broadens, overlaps or separates from another distribution. Reserve words such as expression increased for interpretations supported by controls and the study’s analytical criteria.

A beginner-friendly paragraph might say, “Compared with the control overlay, the tested group has more of its plotted distribution at higher fluorescence signals. Both curves were normalized for display, so their heights do not establish absolute event counts.” Such prose translates the main visual pattern and teaches the reader what cannot be concluded from it. Concision and caution are compatible.

What needs to be kept unchanged in multilingual translations

Instrument channel names, marker symbols, gate IDs, numerical values, percent signs and sample codes deserve special protection. A single-character difference can alter which subpopulation a description refers to. Terms like singlets, viable, double-positive and parent population require local definitions. A target-language sentence should be natural, but its technical relationships should remain stable.

Maintain a bilingual glossary with separate entries for event, cell, gate, parent gate, median fluorescence intensity and compensation. Translating every English word literally can be counterproductive when a field uses established borrowed terminology. The real criterion is whether a specialist in the target language can reconstruct the same measurement and selection logic without having to guess what the original author meant.

A seven-part verification method

First, verify panel identity and sample mapping. Second, verify every axis and transformation. Third, locate the initial event count and the relevant gate hierarchy. Fourth, reconcile each reported percentage with its stated denominator. Fifth, confirm how marker-positive thresholds were defined and which controls are documented. Sixth, review whether comments about biology are actually supported by the experiment. Seventh, check the wording, numerical punctuation and accessibility text against the original plots.

These checks are practical because they follow the structure of the evidence. A fluent translation that moves a percentage from “percent of parent” to “percent of all cells” can create a large quantitative error. A careful reader should be able to point to each phrase in the final prose and find the figure label or method statement that justifies it. That is what scientific verification looks like in written language.

How this topic connects to other image-translation skills

Flow cytometry shares several challenges with other technical chart types. In microscope images, magnification must not be confused with actual specimen size. In calibration curves, detector response must not be confused with concentration. In gel electrophoresis, sample lanes must not be confused with sample identities. Flow cytometry adds a special difficulty: reported populations depend on an explicit succession of analytical gates.

For related reading, see How to Translate Microscope Images and Scale Bars, How to Translate Calibration Curves, and How to Translate Gel Electrophoresis Images. The eduKate accuracy-and-verification guide explains how to compare a source’s evidence and a translated sentence. Cross-Linguistic Vocabulary Transfer offers a broader route for readers navigating several scientific languages.

Frequently asked questions: Are quadrant percentages always out of 100?

A given plot may show four percentages that sum to approximately 100%, depending on which events are included and how the software reports values. But that total generally pertains to the population shown in that plot or the specified parent, not necessarily the raw sample. Rounding can also produce small deviations. Verify the denominator rather than relying on the visual total.

Readers also ask whether a dot always equals one living cell. Not necessarily. A dot commonly represents an event in the displayed dataset, and analysis steps may exclude debris, multiple-cell coincidences or compromised events. The correct language depends on what has already been selected. When in doubt, “events” is the less presumptive term.

Frequently asked questions: Can color identify a cell type?

Color in a software plot frequently represents display density, overlay identity or a gate. It does not inherently correspond to the actual visible color of a cell, and it does not independently confirm a biological classification. Consult the plot legend and the reagent panel. Cell identity in a scientific report is usually supported by combinations of markers, controls and analytical decisions.

Another common question is whether a higher fluorescence value proves more protein in the sample. The response depends on labeling and assay validation. Signal can support conclusions about marker abundance under suitable conditions, but a raw fluorescence shift alone is not a universal direct protein-count measurement. A careful translation retains the method’s own operational language instead of promising more than the experiment measures.

Frequently asked questions: Why can two analysts report different percentages?

Different gating boundaries, event exclusions, compensation settings, controls and denominators can change the selected populations. This does not mean every analysis is arbitrary; it means procedures and definitions must be documented for reproduction and fair comparison. A robust caption reports the relevant gate strategy or points to a method section where readers can find it.

For translation, do not reconcile disagreements by averaging two displayed percentages or choosing whichever is easier to explain. Preserve the reported values and the conditions attached to them. If the source contains a contradiction, flag it for qualified review. The translator’s duty is fidelity to evidence and clarity about uncertainty, not secret correction of laboratory decisions.

Why careful description matters

Flow cytometry seems visual, but its most important relationships are often invisible until the analyst explains them: selected events, parent gates, marker thresholds, compensation and control strategy. An accurate account makes those relationships understandable in plain language. It protects sample identity, measurement axes and the denominator for every reported fraction. It also keeps research plots from being mistaken for clinical verdicts.

Did you know that the same gate can represent 40% of one parent population and only 20% of the originally acquired events? Nothing about the dots needs to change for both statements to be true. The difference is the denominator. Once that idea becomes familiar, flow cytometry descriptions become easier to write, translate and verify. The best translation is the one that lets a reader reconstruct exactly how the reported subset was defined.

How to Translate Easily | How to Translate Flow Cytometry Plots Without Reversing Gates, Fluorescence or Cell Percentages