title: Alternative statistical parameter for high-throughput screening assay quality assessment.
abstract: High-throughput screening is an essential process in drug discovery. The ability to identify true active compounds depends on the high quality of assays and proper analysis of data. The Z factor, presented by Zhang et al. in 1999, provides an easy and useful summary of assay quality and has been a widely accepted standard. However, as data analysis has undergone much improvement recently, the assessment of assay quality has not evolved in parallel. In this article, the authors study the implications of Z factor values under different conditions and link the Z factor with the power of discovering true active compounds. They discuss the different interpretations of Z factor depending on error distributions and advocate direct analysis of power as assay quality assessment. They also propose that in estimating assay quality parameters, adjustments in data analysis should be taken into account. Studying the power of identifying true "hits" gives a more direct interpretation of assay quality and may provide guidance in assay optimization on some occasions.
authors.affiliation: Department of Community Health, Brown University, Providence, RI 02903, USA.
authors.forename: Yunxia
authors.initials: Y
authors.lastname: Sui
authors.forename: Zhijin
authors.initials: Z
authors.lastname: Wu
mesh_terms: D002626:Chemistry, Pharmaceutical; D003627:Data Interpretation, Statistical; D015195:Drug Design; D004353:Drug Evaluation, Preclinical / Q000706:statistics & numerical data*; D015233:Models, Statistical; D015203:Reproducibility of Results; D013329:Structure-Activity Relationship