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首页> 外文期刊>Journal of proteome research >ADAP-GC 3.2: Graphical Software Tool for Efficient Spectral Deconvolution of Gas Chromatography–High-Resolution Mass Spectrometry Metabolomics Data
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ADAP-GC 3.2: Graphical Software Tool for Efficient Spectral Deconvolution of Gas Chromatography–High-Resolution Mass Spectrometry Metabolomics Data

机译:ADAP-GC 3.2:用于高分辨率气相色谱 - 高分辨率质谱代谢组数据的高效光谱去卷积的图形软件工具

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摘要

ADAP-GC is an automated computational workflow for extracting metabolite information from raw, untargeted gas chromatography–mass spectrometry metabolomics data. Deconvolution of coeluting analytes is a critical step in the workflow, and the underlying algorithm is able to extract fragmentation mass spectra of coeluting analytes with high accuracy. However, its latest version ADAP-GC 3.0 was not user-friendly. To make ADAP-GC easier to use, we have developed ADAP-GC 3.2 and describe here the improvements on three aspects. First, all of the algorithms in ADAP-GC 3.0 written in R have been replaced by their analogues in Java and incorporated into MZmine 2 to make the workflow user-friendly. Second, the clustering algorithm DBSCAN has replaced the original hierarchical clustering to allow faster spectral deconvolution. Finally, algorithms originally developed for constructing extracted ion chromatograms (EICs) and detecting EIC peaks from LC–MS data are incorporated into the ADAP-GC workflow, allowing the latter to process high mass resolution data. Performance of ADAP-GC 3.2 has been evaluated using unit mass resolution data from standard-mixture and urine samples. The identification and quantitation results were compared with those produced by ADAP-GC 3.0, AMDIS, AnalyzerPro, and ChromaTOF. Identification results for high mass resolution data derived from standard-mixture samples are presented as well.
机译:ADAP-GC是一种自动计算工作流程,用于从原始,未标准的气相色谱 - 质谱代谢组数据中提取代谢物信息。 Coeluting分析物的去卷积是工作流程中的关键步骤,并且底层算法能够以高精度提取共面分析物的碎片质谱。但是,它的最新版本ADAP-GC 3.0不是用户友好的。为了使ADAP-GC更轻松地使用,我们开发了ADAP-GC 3.2并在此描述了三个方面的改进。首先,在R中编写的ADAP-GC 3.0中的所有算法已被Java中的类似物替换为Mzmine 2,以使工作流用户友好。其次,群集算法DBSCAN已更换原始分层聚类以允许更快的频谱折叠卷积。最后,最初开发用于构造提取的离子色谱图(EIC)和从LC-MS数据检测到EIC峰的算法并入到ADAP-GC工作流程中,允许后者处理高质量分辨率数据。 ADAP-GC 3.2的性能已经使用来自标准混合物和尿液样本的单位质量分辨率数据进行评估。将鉴定和定量结果与ADAP-GC 3.0,AMDIS,Analyserpro和Chromatof产生的鉴定和定量结果进行了比较。还介绍了衍生自标准混合物样品的高质量分辨率数据的鉴定结果。

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