Open AccessComparison of frequency distributions in flow cytometry
Author(s) -
Cox Christopher,
Reeder Jay E.,
Robinson Roy D.,
Suppes Sarah B.,
Wheeless Leon L.
Publication year - 1988
Publication title -
cytometry
Language(s) - English
Resource type - Journals
eISSN - 1097-0320
pISSN - 0196-4763
DOI - 10.1002/cyto.990090404
Subject(s) - poisson distribution , computer science , context (archaeology) , channel (broadcasting) , set (abstract data type) , statistical hypothesis testing , simple (philosophy) , frequency distribution , data set , probability distribution , flow (mathematics) , algorithm , statistics , mathematics , statistical physics , artificial intelligence , physics , paleontology , computer network , philosophy , geometry , epistemology , biology , programming language
A number of methods have previously been considered for the statistical comparison of flow cytometric frequency distributions. For two distributions, the foremost of these is the Kolmogorov‐Smirnov (K‐S) test, which has been criticized as “too sensitive.” We discuss some alternative methods based on the Poisson distribution. The assumption of Poisson variation within channels allows the use of channel‐by‐channel confidence intervals and chi‐square tests. These are simple and more appropriate for discrete data than the K‐S test. Graphical displays of these and other techniques are presented. We also attempt to set the problem in an appropriate context. We argue that any statistical procedure must rest on a reasonable understanding of the nature of the variability in the system. This understanding takes the form of an appropriate probability model, which may be approximate but must provide a reasonably accurate description of the data. Incomplete understanding of the data can lead to inappropriate analysis. We discuss the assumptions that underlie our techniques and consider extensions to more complex situations.