Couprie Camille, Duval Laurent, Moreaud Maxime, Hénon Sophie, Tebib Mélinda, Souchon Vincent
IFP Energies nouvelles, 1-4 avenue de Bois-Préau, 92500 Rueil-Malmaison, France.
IFP Energies nouvelles, 1-4 avenue de Bois-Préau, 92500 Rueil-Malmaison, France; University Paris-Est, LIGM, ESIEE Paris, F-93162 Noisy-le-Grand, France.
J Chromatogr A. 2017 Feb 10;1484:65-72. doi: 10.1016/j.chroma.2017.01.003. Epub 2017 Jan 4.
Two-dimensional gas chromatography (GC×GC) plays a central role into the elucidation of complex samples. The automation of the identification of peak areas is of prime interest to obtain a fast and repeatable analysis of chromatograms. To determine the concentration of compounds or pseudo-compounds, templates of blobs are defined and superimposed on a reference chromatogram. The templates then need to be modified when different chromatograms are recorded. In this study, we present a chromatogram and template alignment method based on peak registration called BARCHAN. Peaks are identified using a robust mathematical morphology tool. The alignment is performed by a probabilistic estimation of a rigid transformation along the first dimension, and a non-rigid transformation in the second dimension, taking into account noise, outliers and missing peaks in a fully automated way. Resulting aligned chromatograms and masks are presented on two datasets. The proposed algorithm proves to be fast and reliable. It significantly reduces the time to results for GC×GC analysis.
二维气相色谱法（GC×GC）在复杂样品的解析中起着核心作用。峰面积识别的自动化对于实现快速且可重复的色谱图分析至关重要。为了确定化合物或准化合物的浓度，定义斑点模板并将其叠加在参考色谱图上。当记录不同的色谱图时，这些模板随后需要进行修改。在本研究中，我们提出了一种基于峰配准的色谱图和模板对齐方法，称为BARCHAN。使用强大的数学形态学工具识别峰。对齐通过沿第一维的刚性变换和第二维的非刚性变换的概率估计来执行，以全自动方式考虑噪声、异常值和缺失峰。在两个数据集上展示了得到的对齐色谱图和掩码。所提出的算法被证明是快速且可靠的。它显著减少了GC×GC分析得出结果的时间。
