Data Analysis Tool for Comprehensive Two-Dimensional Gas Chromatography/Time-of-Flight Mass Spectrometry
Data Analysis Tool for Comprehensive Two-Dimensional Gas Chromatography/Time-of-Flight Mass Spectrometry
复制标题
DOI：
10.1021/ac103308x
复制
发表时间：
2011-04-15
影响因子：
7.4
通讯作者：
Hyotylainen, Tuulia
中科院分区：
文献类型：
--
作者：
Castillo, Sandra;Mattila, Ismo;Hyotylainen, Tuulia
在二维气相色谱-飞行时间质谱联用（GC x GC/TOFMS）分析中，未知化合物的数据处理和鉴定是一项重大挑战，尤其是在分析大样本集时。在这里，我们提出了一种方法，用于有效地处理大型数据集的GC × GC/TOFMS实现作为一个免费的开源软件包，Guineu。为了处理大型数据集并有效利用供应商软件中可用的所有功能（基线校正、质谱去卷积、峰拾取、积分、库搜索和信噪比过滤），使用仪器软件预处理的数据作为进一步处理的起点。我们的软件提供了对齐的数据，归一化，数据过滤，并利用保留指数在验证的识别以及一种新的工具，用于自动组型鉴定的化合物。在此，详细研究了软件的不同功能，并通过分析大量标准样品以及大量真实生物样品（包括对照样品）来验证系统的性能。我们的GC x GC/TOFMS方法的定量特征也进行了研究，以进一步证明该方法的性能和实验结果证实了开发的程序的可靠性。该方法已经成功地用于代谢组学领域的数千个样品的分析。
Data processing and identification of unknown compounds in comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (GC x GC/TOFMS) analysis is a major challenge, particularly when large sample sets are analyzed. Herein, we present a method for efficient treatment of large data sets produced by GC x GC/TOFMS implemented as a freely available open source software package, Guineu. To handle large data sets and to efficiently utilize all the features available in the vendor software (baseline correction, mass spectral deconvolution, peak picking, integration, library search, and signal-to-noise filtering), data preprocessed by instrument software are used as a starting point for further processing. Our software affords alignment of the data, normalization, data filtering, and utilization of retention indexes in the verification of identification as well as a novel tool for automated group-type identification of the compounds. Herein, different features of the software are studied in detail and the performance of the system is verified by the analysis of a large set of standard samples as well as of a large set of authentic biological samples, including the control samples. The quantitative features of our GC x GC/TOFMS methodology are also studied to further demonstrate the method performance and the experimental results confirm the reliability of the developed procedure. The methodology has already been successfully used for the analysis of several thousand samples in the field of metabolomics.