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MS2Planner: improved fragmentation spectra coverage in untargeted mass spectrometry by iterative optimized data acquisition
Author(s) -
Zeyuan Zuo,
Liu Cao,
Louis-Félix Nothia,
Hosein Mohimani
Publication year - 2021
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btab279
Subject(s) - fragmentation (computing) , computer science , mass spectrometry , mass spectrum , python (programming language) , workflow , source code , data mining , chemistry , computational science , algorithm , database , operating system , chromatography
Untargeted mass spectrometry experiments enable the profiling of metabolites in complex biological samples. The collected fragmentation spectra are the metabolite's fingerprints that are used for molecule identification and discovery. Two main mass spectrometry strategies exist for the collection of fragmentation spectra: data-dependent acquisition (DDA) and data-independent acquisition (DIA). In the DIA strategy, all the metabolites ions in predefined mass-to-charge ratio ranges are co-isolated and co-fragmented, resulting in multiplexed fragmentation spectra that are challenging to annotate. In contrast, in the DDA strategy, fragmentation spectra are dynamically and specifically collected for the most abundant ions observed, causing redundancy and sub-optimal fragmentation spectra collection. Yet, DDA results in less multiplexed fragmentation spectra that can be readily annotated.

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