Data from: GlypPRM: An automated analyzer and quantification tool for glycopeptides parallel reaction monitoring

Glycosylation is a prevalent and structurally complex post-translational
modification implicated in diverse biological processes and diseases. Mass
spectrometry (MS)-based glycoproteomics, especially Parallel Reaction
Monitoring (PRM), offers high specificity and quantitative power for
glycopeptide analysis. PRM enables full MS/MS acquisition for targeted
precursors, enhancing signal-to-noise ratios and structural confidence,
key advantages over conventional targeted methods. However, the
identification and quantification of glycopeptides from PRM data remain
challenging due to extensive glycan heterogeneity, site multiplicity, and
complex fragmentation patterns. Existing software platforms often lack
tailored support for glycopeptide-specific fragmentation logic, glycan
structure modeling, or automated spectral interpretation, leaving much of
PRM-based glycoproteomics reliant on manual workflows. To address these
limitations, we developed GlypPRM, a Python-based, fully integrated
platform for automated glycopeptide PRM data analysis. GlypPRM features
theoretical fragment ion simulation, glycan structure prediction, spectral
matching, chromatographic integration, and quantitative analysis for both
N- and O-glycopeptides. We validated its performance using glycopeptides
derived from bovine fetuin and complex human serum samples, demonstrating
high structural accuracy, reproducibility, and interpretability. GlypPRM
also includes advanced visualization, flexible input handling, diagnostic
ion filtering, and publication-ready export formats. This scalable,
glycan- and peptide-aware platform establishes a robust foundation for
high-confidence PRM-based glycoproteomics in biomarker discovery and
disease research.