FlowJo Population Comparison PlatformsįlowJo contains two platforms that allow the direct comparison between different populations, Population Comparison (Uni- and Multivariate) and Multi-sample Comparison. This algorithm has been shown to detect small differences between two populations and it does so in a quantitative way. The PB comparison is related to the Cox chi-square 6 approach, but with modified binning such that it minimizes the maximal expected variance. Caution must be exercised with this statistic as it will erroneously report that two halves of the same population (every other cell makes up one of the halves while the cells in between make up the other half) are distinct.Ī new comparison algorithm was recently developed for the comparison of distributions, called Probability Binning (Chi(T) or PB) (3-5). The Kolmogorov-Smirnov (K-S) algorithm is a commonly used method to determine the confidence interval with which one can make the assertion that two flow cytometric univariate histograms are different. Several algorithms can be used to compare FACS data. The Super-enhanced Dmax Subtraction (SED) is a new sophisticated algorithm by Bruce Bagwell to compute %Positives when comparing histograms. This method does not provide an indication of the probability with which two distributions are different nor does it provide confidence intervals. The Overton cumulative histogram subtraction 1 algorithm essentially subtracts histograms on a channel-by-channel basis to provide a percent of positive cells. Two algorithms (K-S and Chi(T) / PB) are used to determine the statistical difference between samples. Two algorithms (Overton and SED) are used to calculate the percentage of positive cells found in the sample and not the control). Comparison AlgorithmsįlowJo's comparison platforms support four different comparison algorithms. test sample) in order to detect a response, or to provide feedback regarding instrument stability by detecting when collected data varies significantly over time.

For example, to determine whether two samples are statistically significantly different (control vs. Comparing distributions of FACS data is an important goal in many applications.

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