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首页> 外文期刊>Journal of chromatography, A: Including electrophoresis and other separation methods >Automatic program for peak detection and deconvolution of multi-overlapped chromatographic signals - Part I: Peak detection
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Automatic program for peak detection and deconvolution of multi-overlapped chromatographic signals - Part I: Peak detection

机译:多重叠色谱信号的峰检测和去卷积的自动程序-第一部分:峰检测

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摘要

A series of two papers describing a procedure for automated peak deconvolution is presented. The goal is to develop a package of routines that can be used by non-experienced users. Part I (this paper) concerns peak detection, whereas Part II is dedicated to the deconvolution itself. In this first part, the most interesting features of the peak detection algorithms, which precede the deconvolution step, are outlined. High-order derivatives provide valuable information to assess the number of underlying compounds under a given peak cluster. A smoothing technique was found essential to compute properly the derivatives, since the noise is amplified when differences are calculated. The Savitsky-Golay smoother was applied in combination with the Durbin-Watson criterion to automate the window size selection. This strategy removed the noise without loosing valuable information. In some cases, it was found preferable to split the chromatogram in different elution regions, and apply the Durbin-Watson test and the Savitsky-Golay smoother to each region, separately. The derivatives allowed obtaining estimates of both peak parameters and the corresponding ranges for each eluting compound to be used in the deconvolution. An algorithm oriented to compare peaks from different chromatograms is also presented to perform deconvolution, using information from several related chromatograms. (c) 2005 Elsevier B.V. All rights reserved.
机译:提出了一系列两篇论文,描述了自动峰反卷积的过程。目标是开发可供无经验的用户使用的例程程序包。第一部分(本文)涉及峰值检测,而第二部分专门针对反卷积本身。在第一部分中,概述了在去卷积步骤之前的峰值检测算法最有趣的功能。高阶导数可提供有价值的信息,以评估给定峰簇下潜在化合物的数量。发现平滑技术对于正确计算导数至关重要,因为在计算差异时会放大噪声。 Savitsky-Golay平滑器与Durbin-Watson准则组合使用,以自动选择窗口大小。这种策略消除了噪音,而又不会丢失有价值的信息。在某些情况下,发现最好将色谱图拆分为不同的洗脱区域,并分别对每个区域应用Durbin-Watson试验和Savitsky-Golay平滑剂。导数允许获得用于反卷积的每种洗脱化合物的峰参数和相应范围的估计值。还提出了一种用于比较来自不同色谱图的峰的算法,以使用来自几个相关色谱图的信息执行反卷积。 (c)2005 Elsevier B.V.保留所有权利。

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