Z-factor
Before you trust a screen to tell hits from non-hits, you need to know whether the assay can actually tell them apart. The Z-factor is a single number that answers this: it measures how cleanly the 'fully active' and 'fully inactive' control signals separate, accounting for both the gap between their averages and the scatter (noise) around each.
Conceptually, the Z-factor asks how much room is left between the two control populations once you subtract the spread caused by experimental noise. A value of 1 would be a perfect, noise-free separation; values from 0.5 to 1 indicate an excellent assay where signal and background barely overlap; values between 0 and 0.5 are marginal and risky; and values at or below 0 mean the controls overlap so much the assay cannot reliably distinguish a hit from background.
The Z-factor (and its control-only sibling, the Z'-factor) is the standard gatekeeping metric for high-throughput screening: assays are usually required to clear roughly 0.5 before a large campaign proceeds, and it is monitored plate-by-plate to catch drift. It judges robustness, however, not biological relevance — a high Z-factor on a flawed or irrelevant assay still produces tidy, confidently wrong numbers.
During assay development, the positive and negative controls give a Z'-factor of 0.72 across many plates, clearing the bar to launch a million-compound screen.
A high Z'-factor certifies that the assay can reliably separate hits from background.
Roughly: Z ≥ 0.5 is the conventional bar for a screen-worthy assay, 0–0.5 is doable but fragile, and ≤ 0 means the controls overlap too much to trust. The Z'-factor uses only the controls to grade the assay itself, independent of test compounds.