An automatic peak finding method for LC-MS data using Gaussian second derivative filtering
An automatic peak finding method for LC-MS data using Gaussian second derivative filtering
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DOI：
10.1002/jssc.200900395
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发表时间：
2009-11-01
影响因子：
3.1
通讯作者：
Bylund, Dan
中科院分区：
文献类型：
--
作者：
Fredriksson, Mattias J.;Petersson, Patrik;Bylund, Dan
开发了一种高度自动化的程序，用于在LC-MS数据的色谱时域中定位和表征峰。这项工作是由确定的需要，以促进检测和跟踪色谱峰在方法开发过程中分析药品中的杂质。该算法主要基于数字滤波器，其设置自动适应于所研究的数据集。对不同SIN水平、峰宽和基线特性的合成数据集进行了评价。结果发现，即使对于S/N = 10且基线变异性较高的最差情况，也可检出94%的模拟分析峰，而不会产生任何假阳性鉴别。此外，正确估计的峰高和峰宽落在真实值的10%误差内的数量分别为94和91%。对于实验数据集，峰高和宽度估计更困难，但处理后的重建显示出与原始数据的分析信号非常一致，并且在总离子和基峰色谱图中的可视化也明显改善。
A highly automated procedure for localising and characterising peaks in the chromatographic time domain of LC-MS data has been developed. The work was initiated by an identified need to facilitate the detection and tracking of chromatographic peaks during method development for the analysis of impurities in pharmaceutical products. The algorithm is mainly based on a digital filter for which the settings are automatically adapted to the data set under study. The procedure was evaluated for synthetic data sets with various SIN levels, peak widths and baseline proper-ties. It was found that even for the worst case tested with S/N = 10 and a high variability in the baseline, 94% of the simulated analytical peaks could be detected without producing any false-positive identifications. Furthermore, the number of correctly estimated peak heights and peak widths falling within a 10% error of the true values were 94 and 91%, respectively. For experimental data sets, peak height, and width estimations were more difficult, but the processed reconstructions showed an excellent agreement with the analytical signals of the raw data, and also a clearly improved visualisation in total ion- and base-peak chromatograms.