Mathematical relationships between control group variability and assay quality metrics

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Andrew Lim
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引用次数: 0

Abstract

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.

Abstract Image

对照组变异性与测定质量指标之间的数学关系
化验质量指标已用于各种高通量筛选(HTS)活动,以指示化验质量。Z’因子与标准化平均差(SSMD)等其他指标一起,已成为最广泛使用的指标之一。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)和每个对照组内的变异系数(CV)的影响。在本文中,推导了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(用CV和HZ总结)之间的关系。这些方程增加了我们对提高测定质量指标的因素的理解,从而提供了一种定量方法来可视化影响对照组如何影响测定质量指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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