![]() ![]() The proportional nature of contour plots makes them more independent of sample size. Closely packed contour lines indicate a high concentration of events. Each line encloses an equal percentage of events (1). Event densities are depicted with contour lines (gradients). On a contour plot, the relative frequency of data are displayed. When the plot has concentrated high density regions, a contour plot may be more effectual for data presentation. The bunching can obfuscate important details within the data (1). When plotting data from populations with a large amount of variance, the dots may begin to bunch up. In Figure 2, the same scatter parameters and population of 35k events is represented by up to 5k dots.įigure 2. Figure 1 is a dot plot illustrating scatter parameters, and 2k events displayed using up to 2k dots.įigure 1. The data from each event (usually a cell) is binned into histograms, and the most highly populated of those bins are delineated on the plot as dots (1). The optimal method of visualization can be selected based on the nature of the data set.Ī dot plot is helpful when studying populations with moderate or low frequency populations. Both graph types are bivariate (having two axes correspond to different variables). Two common graph types for flow cytometry data are dot and contour plots. The axial parameters are usually some combination of light scatter and fluorescence (1). This information can be displayed within FlowJo ™ by first binning the recorded data in a two dimensional histogram and graphing those bins on an x-y plane (cartesian coordinates). The information collected by the flow cytometer is saved in a special type of list mode data (LMD) file, known as a flow cytometry standard (i.e. ![]() Effective data display enables the reader to accurately interpret displayed information. Data graphical display type is an important choice when performing a flow cytometry workflow. ![]()
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