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Abstract：
There is growing interest in the application of rapid quantitative polymerase chain reaction (qPCR) and other PCR-based methods for recreational water quality monitoring and management programs. This interest has strengthened given the publication of U.S. Environmental Protection Agency (EPA)-validated qPCR methods for enterococci fecal indicator bacteria (FIB) and has extended to similar methods for Escherichia coli (E. coli) FIB. Implementation of qPCR-based methods in monitoring programs can be facilitated by confidence in the quality of the data produced by these methods. Data quality can be determined through the establishment of a series of specifications that should reflect good laboratory practice. Ideally, these specifications will also account for the typical variability of data coming from multiple users of the method. This study developed proposed standardized data quality acceptance criteria that were established for important calibration model parameters and/or controls from a new qPCR method for E. coli (EPA Draft Method C) based upon data that was generated by 21 laboratories. Each laboratory followed a standardized protocol utilizing the same prescribed reagents and reference and control materials. After removal of outliers, statistical modeling based on a hierarchical Bayesian method was used to establish metrics for assay standard curve slope, intercept and lower limit of quantification that included between-laboratory, replicate testing within laboratory, and random error variability. A nested analysis of variance (ANOVA) was used to establish metrics for calibrator/positive control, negative control, and replicate sample analysis data. These data acceptance criteria should help those who may evaluate the technical quality of future findings from the method, as well as those who might use the method in the future. Furthermore, these benchmarks and the approaches described for determining them may be helpful to method users seeking to establish comparable laboratory-specific criteria if changes in the reference and/or control materials must be made.
摘要：
人们对快速定量聚合酶链反应（qPCR）和其他基于PCR的方法用于娱乐水质监测和管理计划的应用越来越感兴趣。鉴于美国环境保护署（EPA）验证的用于肠球菌粪便指示细菌（FIB）的qPCR方法的出版，这种兴趣得到了加强，并且已经扩展到用于大肠杆菌的类似方法（E.大肠杆菌)FIB。基于qPCR的方法在监测程序中的实施可以通过对由这些方法产生的数据的质量的信心来促进。可以通过建立一系列应反映良好实验室实践的规范来确定数据质量。理想情况下,这些规范还将说明来自该方法的多个用户的数据的典型可变性。这项研究开发了提出的标准化数据质量接受标准，这些标准是根据21个实验室生成的数据，从大肠杆菌的新qPCR方法（EPA草案方法C）为重要的校准模型参数和/或对照建立的。每个实验室都遵循使用相同规定试剂以及参考和对照材料的标准化方案。去除异常值后，基于分层贝叶斯方法的统计建模用于建立测定标准曲线斜率的指标，拦截和定量下限，包括实验室之间，在实验室内进行复制测试，和随机误差可变性。嵌套方差分析(ANOVA)用于建立校准物/阳性对照的指标。阴性对照,并复制样本分析数据。这些数据接受标准应有助于那些可能评估该方法未来发现的技术质量的人，以及将来可能使用该方法的人。此外，如果必须更改参考和/或对照材料，则这些基准和用于确定它们的方法可能有助于方法用户寻求建立可比的实验室特定标准。
