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代谢组学实验中用于气相色谱 - 质谱色谱图比对的八个软件程序的比较评估

Comparative evaluation of eight software programs for alignment of gas chromatography-mass spectrometry chromatograms in metabolomics experiments.

作者信息

Niu Weihuan, Knight Elisa, Xia Qingyou, McGarvey Brian D

机构信息

School of Life Science, Chongqing University, Chongqing 400044, China.

Southern Crop Protection and Food Research Centre, Agriculture and Agri-Food Canada, 1391 Sandford Street, London, Ontario N5V 4T3, Canada.

出版信息

J Chromatogr A. 2014 Dec 29;1374:199-206. doi: 10.1016/j.chroma.2014.11.005. Epub 2014 Nov 20.

Abstract

Since retention times of compounds in GC-MS chromatograms always vary slightly from chromatogram to chromatogram, it is necessary to align chromatograms before comparing them in metabolomics experiments. Several software programs have been developed to automate this process. Here we report a comparative evaluation of the performance of eight programs using prepared samples of mixtures of chemicals, and an extract of tomato vines spiked with three concentrations of a mixture of alkanes. The programs included in the comparison were SpectConnect, MetaboliteDetector 2.01a, MetAlign 041012, MZmine 2.0, TagFinder 04, XCMS Online 1.21.01, MeltDB and GAVIN. Samples were analyzed by GC-MS, chromatograms were aligned using the selected programs, and the resulting data matrices were preprocessed and submitted to principal components analysis. In the first trial, SpectConnect, MetAlign and MetaboliteDetector correctly identified ≥90% of the true positives. In the second trial, MetAlign and MetaboliteDetector correctly identified 87% and 81% of the true positives, respectively. In addition, in both trials >90% of the peaks identified by MetAlign and MetaboliteDetector were true positives.

摘要

由于气相色谱 - 质谱联用(GC-MS)色谱图中化合物的保留时间在不同色谱图之间总会略有差异,因此在代谢组学实验中比较色谱图之前,有必要对其进行校准。已经开发了几种软件程序来自动化这一过程。在此,我们报告了使用化学混合物的制备样品以及添加了三种浓度链烷混合物的番茄藤提取物,对八个程序的性能进行的比较评估。参与比较的程序包括SpectConnect、MetaboliteDetector 2.01a、MetAlign 041012、MZmine 2.0、TagFinder 04、XCMS Online 1.21.01、MeltDB和GAVIN。通过GC-MS对样品进行分析,使用选定的程序对色谱图进行校准,并对所得数据矩阵进行预处理,然后进行主成分分析。在第一次试验中,SpectConnect、MetAlign和MetaboliteDetector正确识别出≥90%的真阳性。在第二次试验中,MetAlign和MetaboliteDetector分别正确识别出87%和81%的真阳性。此外,在两次试验中,MetAlign和MetaboliteDetector识别出的峰中>90%是真阳性。

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