These are histograms that display a single measurement parameter (relative fluorescence or light scatter intensity) on the x-axis and the number of events (cell count) on the y-axis.
The histogram in Figure 14 looks very basic but is useful for evaluating the total number of cells in a sample that possesses the physical properties selected for or which express the marker of interest. Cells with the desired characteristics are known as the positive dataset.
Figure. 14. A single-parameter histogram. FITC, fluorescein isothiocyanate.
Ideally, flow cytometry will produce a single distinct peak that can be interpreted as the positive dataset. However, in many situations, flow analysis is performed on a mixed population of cells, resulting in several peaks on the histogram. In order to identify the positive dataset, flow cytometry should be repeated in the presence of an appropriate control (Figure 15).
Figure. 15. Which is the positive dataset? A, using rat anti-mouse F4/80 conjugated to FITC to stain mouse peritoneal macrophages produces two peaks. B, by running an appropriate control (rat IgG2b negative control conjugated to FITC) and overlaying its image on the histogram (blue peak), the positive dataset is identified as the taller purple peak on the right. FL, fluorescence.
Analytical software packages that accompany flow cytometry instruments make measuring the percentage of positive-staining cells in histograms easy. For example, the F4/80 histogram is shown again in Figure 16 with statistics for R3 and R4 (known on this type of graph as bar regions).
Figure. 16. Statistical analysis. FL, fluorescence.
In Figure 16, 100.00% of the negative control (blue peak) is in R4, and 27.82% of cells stain negative for F4/80 (R4) compared to 71.82% in the positive dataset (R3). Additional statistics about the peaks (median and standard deviation) are also provided automatically here, but this will vary with the software. A similar type of analysis will be generated for two-parameter histograms.
Gates and Regions
Two-Parameter or Bivariate Histograms
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