Cross-correlation for flow cytometric histogram background subtractions

Background subtraction is a widely encountered problem in flow cytometry applications for which the currently available analysis techniques are unsatisfactory. The 99% division line method, also referred to as the threshold or marker method, is widely used because it is computationally simple but it has poor accuracy and tends to underestimate the percentage of positive cells when there is overlap between histograms. Model-based approaches are preferred when there are overlapping peaks, but these methods require curve fitting and strong assumptions regarding the shape of the underlying distributions. This report assesses a mathematically rigorous, computationally facile, non-parametric technique called cross correlation for the background subtraction problem. A metric, positivity, derived from cross correlation is shown to overcome the disadvantages of both the 99% division line and model-based methods without compromise. Copyright (C) 2000 Elsevier Science B.V.