A pragmatic approach to the analysis of DNA histograms with a definable G1 peak

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Abstract
A method for DNA histogram analysis is described that depends only on the simple assumption that the data are normally distributed and a requirement that a G1 peak is present. A probability density function was derived from the assumption that extracted the S-phase component from the whole histogram. The model was tested with simulated data, and good agreement between predicted and known proportions in G1, S, and G1+M was found. Good agreement was also found between duplicates of experimentally derived data. Some systematic errors are present in the analysis of certain types of histograms. However, these result in small errors when compared with biological and experimental variation and are less than the average of algorithms in current use. The program required only two queued requests, those of the start and the end channels over which the analysis is to be performed. The algorithms perform rapidly on a micro-computer with only 28K addressable memory. Only two failures occurred in over 350 analyses and the method can be used for drug- and radiation-perturbed populations as well as with unperturbed.