Lim Andrew
The ALBORADA Drug Discovery Institute, University of Cambridge, Island Research Building, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0AH, UK.
SLAS Discov. 2023 Jul;28(5):203-210. doi: 10.1016/j.slasd.2023.02.003. Epub 2023 Feb 24.
Assay quality metrics have been used in various high-throughput screening (HTS) campaigns to indicate assay quality. Z'-factor has become one of the most widely used metrics, along with other metrics such as standardised mean difference (SSMD). In using these metrics, it is important to understand how these metrics can be impacted by the separation between control groups (indicated by the HZ ratio) and the coefficient of variation (CV) within each control group. In this paper, several mathematical equations have been derived to understand the relationship between assay quality metrics (such as Z'-factor and SSMD) and control group datasets (summarised by CV and HZ). These equations increase our understanding of the factors that improve assay quality metrics, thus providing a quantitative means to visualise how affecting control groups can impact assay quality metrics.
分析质量指标已被用于各种高通量筛选(HTS)活动中以指示分析质量。Z'因子已成为使用最广泛的指标之一,其他指标如标准化平均差异(SSMD)也是如此。在使用这些指标时,重要的是要了解这些指标如何受到对照组之间的分离(由HZ比率表示)以及每个对照组内的变异系数(CV)的影响。在本文中,已经推导出几个数学方程来理解分析质量指标(如Z'因子和SSMD)与对照组数据集(由CV和HZ总结)之间的关系。这些方程加深了我们对改善分析质量指标的因素的理解,从而提供了一种定量方法来直观显示影响对照组如何影响分析质量指标。