Improved Monoisotopic Mass Estimation for Deeper Proteome Coverage
Author(s) -
Ramin Rad,
Jiaming Li,
Julian Mintseris,
Jeremy D. O’Connell,
Steven P. Gygi,
Devin K. Schweppe
Publication year - 2020
Publication title -
journal of proteome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.644
H-Index - 161
eISSN - 1535-3907
pISSN - 1535-3893
DOI - 10.1021/acs.jproteome.0c00563
Subject(s) - monoisotopic mass , proteome , proteomics , peptide , identification (biology) , computational biology , mass spectrometry , computer science , chemistry , chromatography , biology , biochemistry , botany , gene
Accurate assignment of monoisotopic peaks is essential for the identification of peptides in bottom-up proteomics. Misassignment or inaccurate attribution of peptidic ions leads to lower sensitivity and fewer total peptide identifications. In the present work, we present a performant, open-source, cross-platform algorithm, Monocle, for the rapid reassignment of instrument-assigned precursor peaks to monoisotopic peptide assignments. We demonstrate that the present algorithm can be integrated into many common proteomic pipelines and provides rapid conversion from multiple data source types. Finally, we show that our monoisotopic peak assignment results in up to a twofold increase in total peptide identifications compared to analyses lacking monoisotopic correction and a 44% improvement over previous monoisotopic peak correction algorithms.
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