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Prediction, detection, and validation of isotope peaks in mass spectrometry data (Supplemental data for manuscript)

ABSTRACT: Mass spectrometry is a key analytical platform for metabolomics. The precise quantification and identification of small molecules is a prerequisite for elucidating the metabolism and the detection, validation, and evaluation of isotope clusters in LC-MS data is important for this task. Here, we present an approach for the improved detection of isotope clusters using chemical prior knowledge and the validation of detected isotope clusters depending on the substance mass using database statistics. We find remarkable improvements regarding the number of detected isotope clusters and are able to predict the correct molecular formula in the top three ranks in 92% of the cases. We make our methodology freely available as part of the Bioconductor packages xcms and CAMERA.

INSTRUMENT(S): micrOTOF-Q II ESI-Qq-TOF (Bruker)

SUBMITTER: Steffen Neumann

PROVIDER: MTBLS381 | MetaboLights | 2016-10-30

REPOSITORIES: MetaboLights

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			Action	DRS
	MTBLS381	Other
	FILES	Other
	a_MTBLS381_metabolite_profiling_mass_spectrometry_positive.txt	Txt
	files-all.json	Other
	i_Investigation.txt	Txt

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