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Appropriate Degree of Trust: Deriving Confidence Metrics for Automatic Peak Assignment in High-Resolution Mass Spectrometry

机译:适当的信任度:高分辨率质谱中自动峰分配的置信度度量

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摘要

Techniques for deriving confidence metrics for the reliability of automatically assigned elemental formulas in complex spectra, from high-resolution mass spectrometers, are described. These metrics can help an analyst to place an appropriate degree of trust in the results obtained from automated spectral analysis of, for example, natural organic materials. To provide these metrics of confidence, common mass spectrometric tests for reliability of peak assignment (mass accuracy/error, relative ion abundance, and rings-plus-double-bonds equivalence) are combined with novel confidence metrics based on the interconnectivity and consistency of a mass difference or mass defect based peak inference network and on the confidence of the initial library matches. These are shown to provide improved peak assignment confidence over manual or simple automatic assignment methods.
机译:描述了从高分辨率质谱仪推导复杂光谱中自动分配的元素公式的可靠性的置信度度量的技术。这些度量可以帮助分析人员对从例如天然有机材料的自动光谱分析获得的结果给予适当的信任度。为了提供这些置信度指标,将基于峰的可靠性(质量准确度/误差,相对离子丰度和环加双键当量)的常规质谱测试与新颖的置信度指标结合起来,基于质量差异或质量缺陷基于峰推断网络并基于初始库匹配的置信度。与手动或简单自动分配方法相比,这些方法可提供更高的峰分配置信度。

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