CAMERA: an integrated strategy for compound spectra extraction and annotation of liquid chromatography/mass spectrometry data sets.
CAMERA: an integrated strategy for compound spectra extraction and annotation of liquid chromatography/mass spectrometry data sets.
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DOI：
10.1021/ac202450g
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发表时间：
2012-01-03
影响因子：
7.4
通讯作者：
Neumann, Steffen
中科院分区：
文献类型：
--
作者：
Kuhl, Carsten;Tautenhahn, Ralf;Boettcher, Christoph;Larson, Tony R.;Neumann, Steffen
液相色谱-质谱联用通常用于代谢组学实验。与相当常规和自动化的数据采集步骤相比，随后的化合物注释和鉴定需要大量的手动分析，因此形成了数据解释的主要瓶颈。在这里，我们提出了相机，一个Bioconductor包集成算法提取化合物光谱，注释同位素和加合物峰，并提出准确的化合物质量，即使在高度复杂的数据。为了评估这些算法，我们将CAMERA的注释与手动定义的注释进行了比较，该注释是针对以不同浓度掺入复杂基质中的已知化合物的混合物。CAMERA在正离子和负离子模式下分别成功提取了89.7%和90.3%的可注释化合物的准确质量。此外，我们提出了一种新的注释方法，结合在相反的离子模式下获得的数据的光谱信息，以进一步提高注释率。我们证明了CAMERA在两个不同的，易于采用的植物代谢组学实验中的效用，其中CAMERA的应用大大减少了手动分析的量。
Liquid chromatography coupled to mass spectrometry is routinely used for metabolomics experiments. In contrast to the fairly routine and automated data acquisition steps, subsequent compound annotation and identification require extensive manual analysis and thus form a major bottle neck in data interpretation. Here we present CAMERA, a Bioconductor package integrating algorithms to extract compound spectra, annotate isotope and adduct peaks, and propose the accurate compound mass even in highly complex data. To evaluate the algorithms, we compared the annotation of CAMERA against a manually defined annotation for a mixture of known compounds spiked into a complex matrix at different concentrations. CAMERA successfully extracted accurate masses for 89.7% and 90.3% of the annotatable compounds in positive and negative ion mode, respectively. Furthermore, we present a novel annotation approach that combines spectral information of data acquired in opposite ion modes to further improve the annotation rate. We demonstrate the utility of CAMERA in two different, easily adoptable plant metabolomics experiments, where the application of CAMERA drastically reduced the amount of manual analysis.
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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
DOI：
10.1093/bioinformatics/btr079
发表时间：
2011-04-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Brown M;Wedge DC;Goodacre R;Kell DB;Baker PN;Kenny LC;Mamas MA;Neyses L;Dunn WB
通讯作者：
Dunn WB
影响因子：
7.4
作者：
Ipsen, Andreas;Want, Elizabeth J.;Lindon, John C.;Ebbels, Timothy M. D.
通讯作者：
Ebbels, Timothy M. D.
影响因子：
1.8
作者：
YERGEY, JA
通讯作者：
YERGEY, JA
影响因子：
2.4
作者：
Raghavan, Usha Nandini;Albert, Reka;Kumara, Soundar
通讯作者：
Kumara, Soundar