title: Statistical analysis of systematic errors in high-throughput screening.
abstract: High-throughput screening (HTS) is an efficient technology for drug discovery. It allows for screening of more than 100,000 compounds a day per screen and requires effective procedures for quality control. The authors have developed a method for evaluating a background surface of an HTS assay; it can be used to correct raw HTS data. This correction is necessary to take into account systematic errors that may affect the procedure of hit selection. The described method allows one to analyze experimental HTS data and determine trends and local fluctuations of the corresponding background surfaces. For an assay with a large number of plates, the deviations of the background surface from a plane are caused by systematic errors. Their influence can be minimized by the subtraction of the systematic background from the raw data. Two experimental HTS assays from the ChemBank database are examined in this article. The systematic error present in these data was estimated and removed from them. It enabled the authors to correct the hit selection procedure for both assays.
authors.affiliation: Laboratoire LACIM, Université du Québec à Montréal, Canada.
authors.forename: Dmytro
authors.initials: D
authors.lastname: Kevorkov
authors.forename: Vladimir
authors.initials: V
authors.lastname: Makarenkov
mesh_terms: D000465:Algorithms; D001331:Automation; D002626:Chemistry, Pharmaceutical; D019295:Computational Biology / Q000379:methods; D004353:Drug Evaluation, Preclinical / Q000379:methods; D020407:Internet; D015233:Models, Statistical; D016011:Normal Distribution; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011786:Quality Control; D015203:Reproducibility of Results; D012984:Software; D013223:Statistics as Topic / Q000379:methods; D013678:Technology, Pharmaceutical; D013997:Time Factors