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A Novel Strategy for Extracted Ion Chromatogram Extraction to Improve Peak Detection in UPLC–HRMS


Extracted ion chromatogram (EIC) extraction is the primary and fundamental step in ultraperformance liquid chromatography–high resolution mass spectrometry (UPLC–HRMS). Unfortunately, researches on this aspect are far beyond to satisfy routine analysis. To address this problem, we provide AiCN–EIC, a novel adaptive ion-connecting network-based strategy for EIC extraction. In this strategy, ions are sorted on the basis of their m/z values and are then connected to form EIC clusters in accordance with m/z differences. An EIC cluster is constructed by placing ions at the corresponding positions of a cluster in accordance with their scan numbers. A multiscale Gaussian smoothing-based peak detection strategy is introduced after bad EICs are removed. We use two datasets to evaluate the performance of AiCN–EIC. Results indicate that AiCN–EIC can efficiently extract EICs from the results of UPLC–HRMS while exhibiting the advantages of insensitivity to m/z tolerance and threshold value in data acquisition. Quantitative results confirm that the performance of our developed strategy is comparable with that of several state-of-the-art methods. AiCN–EIC has been added into the recently developed Matlab GUI toolbox for UPLC–HRMS-based metabolomics, which can be obtained from http://software.tobaccodb.org/software/aicneic.

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Publication details

The article was received on 21 Aug 2018, accepted on 28 Sep 2018 and first published on 28 Sep 2018

Article type: Paper
DOI: 10.1039/C8AY01850B
Citation: Anal. Methods, 2018, Accepted Manuscript
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    A Novel Strategy for Extracted Ion Chromatogram Extraction to Improve Peak Detection in UPLC–HRMS

    P. Lu, M. Fan, Q. Zhang, Q. Zheng, P. Liu, B. Wang, J. Guo, S. Wang, H. Fu, Y. Yu and Y. She, Anal. Methods, 2018, Accepted Manuscript , DOI: 10.1039/C8AY01850B

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