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用于液相色谱自动解释方法开发工具的峰跟踪算法。

Peak-Tracking Algorithm for Use in Automated Interpretive Method-Development Tools in Liquid Chromatography.

作者信息

Pirok Bob W J, Molenaar Stef R A, Roca Liana S, Schoenmakers Peter J

机构信息

van 't Hoff Institute for Molecular Sciences, Analytical Chemistry Group , University of Amsterdam , Science Park 904 , 1098 XH Amsterdam , The Netherlands.

TI-COAST , Science Park 904 , 1098 XH Amsterdam , The Netherlands.

出版信息

Anal Chem. 2018 Dec 4;90(23):14011-14019. doi: 10.1021/acs.analchem.8b03929. Epub 2018 Nov 15.

DOI:10.1021/acs.analchem.8b03929
PMID:30396266
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6282104/
Abstract

A peak-tracking algorithm for chromatograms recorded using liquid chromatography and mass spectrometry was developed. Peaks are tracked across chromatograms using the spectrometric information, the statistical moments of the chromatographic peaks, and the relative retention. The algorithm can be applied to pair chromatographic peaks in two very different chromatograms, obtained for different samples using different methods. A fast version of the algorithm was specifically tailored to process chromatograms obtained during method development or optimization, where a few similar mobile-phase-composition gradients (same eluent components, but different ranges and programming rates) are applied to the same sample for the purpose of obtaining model parameters to describe the retention of sample components. Due to the relative similarity between chromatograms, time-saving preselection protocols can be used to locate a candidate peak in another chromatogram. The algorithm was applied to two different samples featuring isomers. The automatically tracked peaks and the resulting retention parameters generally yielded prediction errors of less than 1%.

摘要

开发了一种用于处理液相色谱和质谱联用记录的色谱图的峰跟踪算法。利用光谱信息、色谱峰的统计矩和相对保留时间在不同色谱图之间跟踪峰。该算法可用于匹配两张差异很大的色谱图中的色谱峰,这两张图是使用不同方法对不同样品得到的。该算法的快速版本经过专门调整,用于处理方法开发或优化过程中获得的色谱图,在此过程中,为了获得描述样品组分保留情况的模型参数,会将几个相似的流动相组成梯度(相同的洗脱液成分,但范围和程序速率不同)应用于同一样品。由于色谱图之间具有相对相似性,因此可以使用节省时间的预选方案在另一张色谱图中定位候选峰。该算法应用于两个含有异构体的不同样品。自动跟踪的峰以及由此得到的保留参数通常产生的预测误差小于1%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9358/6282104/6e43634d6934/ac-2018-039297_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9358/6282104/ff52f4fedea7/ac-2018-039297_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9358/6282104/482437bd5ef4/ac-2018-039297_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9358/6282104/48aa347c9cdd/ac-2018-039297_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9358/6282104/728a46a82df9/ac-2018-039297_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9358/6282104/6e43634d6934/ac-2018-039297_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9358/6282104/ff52f4fedea7/ac-2018-039297_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9358/6282104/482437bd5ef4/ac-2018-039297_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9358/6282104/48aa347c9cdd/ac-2018-039297_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9358/6282104/728a46a82df9/ac-2018-039297_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9358/6282104/6e43634d6934/ac-2018-039297_0005.jpg

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