Data dependent peak model based spectrum deconvolution for analysis of high resolution LC-MS data.
Data dependent peak model based spectrum deconvolution for analysis of high resolution LC-MS data.
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DOI：
10.1021/ac403803a
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发表时间：
2014-02-18
影响因子：
7.4
通讯作者：
Zhang, Xiang
中科院分区：
文献类型：
--
作者：
Wei, Xiaoli;Shi, Xue;Kim, Seongho;Patrick, Jeffrey S.;Binkley, Joe;Kong, Maiying;McClain, Craig;Zhang, Xiang
建立了一种基于数据相关峰模型（DDPM）的高分辨LC-MS光谱解卷积方法。为了构建选择离子色谱图（XIC），将聚类方法（基于密度的噪声应用空间聚类（DBSCAN））应用于LC-MS数据集的所有m/z值，以将m/z值分组到每个XIC中。DBSCAN构造XIC而不需要用户定义的m/z变化窗口。在XIC构建之后，使用一阶和二阶导数测试检测每个XIC中的分子离子的峰，然后使用优化的色谱峰模型选择方法进行峰去卷积。总共考虑了六种色谱峰模型，包括高斯模型、对数正态模型、泊松模型、伽玛模型、指数修正高斯模型以及指数和高斯模型的混合模型。选择丰富的非重叠峰，以找到最佳的峰模型，这是数据和保留时间依赖。对18个加标液相色谱-质谱数据的分析表明，所提出的DDPM光谱反卷积方法优于传统方法。平均而言，DDPM方法不仅从每个测试LC-MS数据中检测到58个色谱峰，而且保留时间和峰面积分别提高了3%和6%。
A data dependent peak model (DDPM) based spectrum deconvolution method was developed for analysis of high resolution LC-MS data. To construct the selected ion chromatogram (XIC), a clustering method, the density based spatial clustering of applications with noise (DBSCAN), is applied to all m/z values of an LC-MS data set to group the m/z values into each XIC. The DBSCAN constructs XICs without the need for a user defined m/z variation window. After the XIC construction, the peaks of molecular ions in each XIC are detected using both the first and the second derivative tests, followed by an optimized chromatographic peak model selection method for peak deconvolution. A total of six chromatographic peak models are considered, including Gaussian, log-normal, Poisson, gamma, exponentially modified Gaussian, and hybrid of exponential and Gaussian models. The abundant nonoverlapping peaks are chosen to find the optimal peak models that are both data- and retention-time-dependent. Analysis of 18 spiked-in LC-MS data demonstrates that the proposed DDPM spectrum deconvolution method outperforms the traditional method. On average, the DDPM approach not only detected 58 more chromatographic peaks from each of the testing LC-MS data but also improved the retention time and peak area 3% and 6%, respectively.
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影响因子：
3
作者：
Sturm M;Bertsch A;Gröpl C;Hildebrandt A;Hussong R;Lange E;Pfeifer N;Schulz-Trieglaff O;Zerck A;Reinert K;Kohlbacher O
通讯作者：
Kohlbacher O
在综合二维气相色谱时质谱法中计算二维保留指数的一种方法。
DOI：
10.1016/j.chroma.2011.02.072
发表时间：
2011-05-06
期刊：
Journal of chromatography. A
影响因子：
--
作者：
Zhao Y;Zhang J;Wang B;Kim SH;Fang A;Bogdanov B;Zhou Z;McClain C;Zhang X
通讯作者：
Zhang X
影响因子：
7.4
作者：
Wei, Xiaoli;Sun, Wenlong;Shi, Xue;Koo, Imhoi;Wang, Bing;Zhang, Jun;Yin, Xinmin;Tang, Yunan;Bogdanov, Bogdan;Kim, Seongho;Zhou, Zhanxiang;McClain, Craig;Zhang, Xiang
通讯作者：
Zhang, Xiang
影响因子：
6.2
作者：
GRIMALT, J;ITURRIAGA, H;OLIVE, J
通讯作者：
OLIVE, J
影响因子：
6.2
作者：
Zhang X;Fang A;Riley CP;Wang M;Regnier FE;Buck C
通讯作者：
Buck C