( and negative controls are equal: ...)Is Z' factor the best assessment for the quality of cellular assays delivering higher content?

Although the assumption that standard deviations of positive and negative controls are equal is not always true, we have observed that actual data correspond fairly well to this model relationship. A plot of the relationship between S:N (method B) and Z factor is shown in Figure 4 together with the actual data from an EGFPNFATc1 translocation assay we have developed. The actual data show a very good correlation to the theoretical curve.

As the results in Figure 5 demonstrate, this relationship holds true for a variety of cell-based assays, including FYVE, AKT-1, PLCd-PH, Rac-1, MAPKAP-k2, SMAD2 and NFATc1 (all GFPbased assays performed in live cells).

It can be seen from Figures 4 and 5 that, while Z factor may be a sensitive indicator of assay performance at the lower end of the performance scale (i.e. Z < 0.5, S:N < 8), S:N may be a more sensitive indicator at the higher end of the performance scale. As S:N increases, Z factor approaches 1 asymptotically, making it an increasingly less sensitive measure of performance improvement. For example, the arrows in Figure 5 indicate two assays whose performance could not confidently be distinguished on the basis of Z factor, but which have distinctly different S:N values. Both metrics of assay performance (Z factor and S:N) therefore may be useful in optimizing assay performance.

Ref: Zhang et al J. Biomol. Screening 4, 67-73, 1999.

Acknowledgement
The authors gratefully acknowledge members of the Molecular Cell Biology Department, Amersham Biosciences, Cardiff, for providing data from a range of cell-based asssays. We also extend our thanks to Bob Nadon (McGill University) for his expert technical advice.

CONCLUSION
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