Calculate Z'-factor of assay quality
Details
The most common way to measure the quality of an assay is the so-called Z'-factor, which describes the separation of the positive and negative control in terms of their standard deviations \(\sigma_p\) and \(\sigma_n\). The Z'-factor is defined as Ji-Hu Zhang et al., A simple statistical parameter for use in evaluation and validation of high throughput screening assays. $$Z' = 1 - (3 * (\sigma_p+\sigma_n))/|\mu_p-\mu_n|$$
where \(\mu_p\) and \(\mu_p\) is the mean value of the positive (response expected) and negative (no response expected) control, respectively. Therefore, the assay quality is independent of the shape of the concentration response curve and solely depend on two control values.
Note, the nConc highest concentrations are assumed as positive control,
whereas the nConc lowest concentrations are used as negative.
| Value | Interpretation |
| Z' ~ 1 | perfect assay |
| 1 > Z' > 0.5 | excellent assay |
| 0.5 > Z' > 0 | moderate assay |
| Z' = 0 | good only for yes/no response |
| Z' < 0 | unacceptable |
Examples
# see example for `fitCurve()` to see how this data was generated
data(Blank2022res)
calculateZPrime(Blank2022res, nConc = 2)
#> [1] -3.237607219 -1.252868716 -5.541275313 -4.970064620 -1.631465147
#> [6] -0.957522437 -0.223832609 -0.902466878 -1.017670816 -1.058958794
#> [11] -1.562843832 -2.115946846 -0.024041256 -0.812729462 -0.691440743
#> [16] -0.009526589 0.030512012 0.077456813 0.266325098 0.216154352
#> [21] 0.151846342 0.140734203 -0.020104856