Statistical analysis of systematic errors in high-throughput screening
Statistical analysis of systematic errors in high-throughput screening
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DOI：
10.1177/1087057105276989
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发表时间：
2005-09-01
影响因子：
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通讯作者：
Makarenkov, V
中科院分区：
文献类型：
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作者：
Kevorkov, D;Makarenkov, V
高通量药物筛选是一种高效的药物发现技术。它允许每次筛选每天筛选超过100，000种化合物，并需要有效的质量控制程序。作者开发了一种用于评估HTS测定的背景表面的方法;该方法可用于校正原始HTS数据。考虑到可能影响命中选择过程的系统误差，这种校正是必要的。所描述的方法允许一个分析实验HTS数据，并确定相应的背景表面的趋势和局部波动。对于具有大量板的测定，背景表面与平面的偏差是由系统误差引起的。通过从原始数据中减去系统背景，可以将它们的影响降至最低。本文对ChemBank数据库中的两个实验HTS检测进行了研究。对这些数据中存在的系统误差进行了估计并从中删除。它使作者能够纠正两种检测试剂盒的命中选择程序。
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.