Analytical Error Reduction Using Single Point Calibration for Accurate and Precise Metabolomic Phenotyping
Analytical Error Reduction Using Single Point Calibration for Accurate and Precise Metabolomic Phenotyping
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DOI：
10.1021/pr900499r
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发表时间：
2009-11-01
影响因子：
4.4
通讯作者：
Jellema, Renger H.
中科院分区：
文献类型：
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作者：
van der Kloet, Frans M.;Bobeldijk, Ivana;Jellema, Renger H.
在大规模代谢组学研究中，由于所选择的平台对许多代谢物的性能不佳和仪器漂移造成的分析误差是一个主要问题。特别是基于质谱的方法，在代谢组学中越来越普遍，如果没有合适的标记内部标准和校准标准，即使在一个实验室内也很难控制分析数据的质量。在本文中，我们提出了一种工作流程，可以使用汇集的校准样本和多个内部标准策略来显着减少分析误差。在批量校准技术之间和内部，分析误差显着减少（增加25%的峰值，RSD低于20%），并且不会妨碍或干扰最终数据的统计分析。
Analytical errors caused by suboptimal performance of the chosen platform for a number of metabolites and instrumental drift are a major issue in large-scale metabolomics studies. Especially for MS-based methods, which are gaining common ground within metabolomics, it is difficult to control the analytical data quality without the availability of suitable labeled internal standards and calibration standards even within one laboratory. In this paper, we suggest a workflow for significant reduction of the analytical error using pooled calibration samples and multiple internal standard strategy Between and within batch calibration techniques are applied and the analytical error is reduced significantly (increase of 25% of peaks with RSD lower than 20%) and does not hamper or interfere with statistical analysis of the final data.