期刊
ANALYTICAL CHEMISTRY
卷 84, 期 1, 页码 283-289出版社
AMER CHEMICAL SOC
DOI: 10.1021/ac202450g
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资金
- California Institute of Regenerative Medicine [TR1-01219]
- National Institutes of Health [R24 EY017540-04, P30 MH062261-10, P01 DA026146-02]
- Department of Energy [FG02-07ER64325, DE-AC0205CH11231]
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 bottleneck 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 modes, 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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