DNA histogram interpretation based on statistical approaches

Abstract

Image cytometric DNA measurements provide data which are most often interpreted as equivalent to the chromosomal ploidy although the chromosomal and the DNA ploidy are not identical. The common link between them is the cell cycle. Therefore, if destined for DNA ploidy interpretations, the DNA cytometry should be performed on a population-oriented stochastic basis. Using stochastic sampling the data can be interpreted by applying the rules of stochastic processes. A set of statistical methods is given that enables a DNA histogram to be interpreted objectively and without human interaction. These statistics analyse the precision and accuracy of the entire measurement process. They give in error probabilities for accepting a measurement as reliable, for recognition of stemlines, stemline aneuploidy, and for evaluating so-called rare events. Nearly 300 image cytometric DNA measurements from breast cancers and rat liver imprints examples have been selected to demonstrate the efficiency of the statistics in each step of interpreting DNA histograms.