Fig. 5: Library-based virtual match-between-run quantification dramatically improves the identification and quantification of glycopeptides for new acquired data.

a Workflow of the evaluation process. An MS1 feature library is built using the features from the discovery dataset identifications, and applied to library-based quantification method on the verification dataset. b Bar plot of library-based quantification sensitivity evaluation result. Upper: number of quantified site-specific glycans (SSG) from library-based quantification. Bottom: number of quantified site-specific glycans from conventional identified-MS2-based quantification method. c Bar plot of library-based quantification confidence evaluation result. Blue: the number of “theoretically matchable profiles” (profiles that can be matched in both library-based quantification and MS2 identification). Orange: the number of un-matched theoretically matchable profiles (profiles whose features are preserved in the library and could also be directly identified by MS2 spectra, but not matched from library-based quantification).