We are now in reasonably good shape to start analysing our data using the various criteria and procedures considered in the previous chapters. In fact, a considerable quantity of such analytical work has been carried out in the analysis of DNA histograms, as will be seen in the next chapter. In contrast, very little comparable analytical work has been performed for immunofluorescence data, but this is becoming increasingly necessary in order to resolve populations in close proximity.

The discrepancy in the quantity of analytical work carried out in these two major areas of flow cytometry (FCM) stems from the backgrounds of the people involved in those areas. The DNA histogram–analysis fraternity has hailed from cell kinetics and mathematical modelling, and these people are au fait with deconvoluting overlapping histograms. The immunofluorescence people tend to have purely biological backgrounds with little mathematical or statistical insight. As always, with any sweeping generalization there are exceptions; however, I'm sure the majority of immunologists (which in this context is more than 50%) would agree with me.

The difference has been one of overall approach. The DNA histogram people have been compelled to deconvolute histograms because the biology “overlaps” at the G1/S and S/G2+M interfaces. In contrast the immunologists, very worthily, have sought to improve their reagents and techniques in order to gain an increase in the signal-to-noise ratio in an effort to more efficiently pull apart populations in close proximity.