Data analysis and presentation in flow cytometry

Abstract

The advancement of flow cytometry technology together with a series of novel developments in hardware and software have facilitated both phenotypic and functional characterizations of different cell types. In addition, the availability of many monoclonal antibodies and an expanding range of dye-chemistry have made multi-parameter flow cytometry possible for simultaneous measurements of large numbers of cells with better information of complex cellular networks such as the immune system. Although it has the advantage of being a fast, objective and quantitative, but running polychromatic flow cytometry is a complex process with many challenges particularly in the data analysis. The purpose of this communication is to describe several types of presentation and analysis of both univariate and multivariate datasets.

Flow cytometry: Aspects and application in plant and biological science

“…The distribution of a single measurement parameter is displayed with the help of a graph known as a univariate histogram. The x‐axis represents the measurement parameter, while the y‐axis represents the cell count, or total number of occurrences [100]. A histogram represents the data, which might represent the entire set of data or only a subset (gated) of it.…”

Flow Cytometry: From Experimental Design to Its Application in the Diagnosis and Monitoring of Respiratory Diseases

“…The contour plot shows the relative intensity distribution by density in circumferences; events with little variation in the evaluated parameter are placed in the centre and events with greater variation are placed outside [ 32 ].…”