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BioinformaticsBioinformatics Advances
Peer-reviewed journal article

GlycoTraitR: an R package for characterizing structural heterogeneity in N-linked glycoproteomics data

Bingyuan ZhangiD, Koichi HimoriiD, Yusuke MatsuiiD

Abstract

Glycoproteomics data are rapidly accumulating due to advances in mass spectrometry instrumentation and the development of specialized search engines (e.g., pGlyco3, Glyco-Decipher) that enable identification of N-linked glycopeptide spectral matches (GPSMs) together with glycan structures. These advances have greatly expanded the scale and depth of N-linked glycopeptides; however, the intrinsic structural heterogeneity of glycosylation remains challenging to interpret. No existing tool provides a unified trait-based framework for analyzing N-linked GPSM data at both the glycosylation-site and protein levels. We developed glycoTraitR, an R package for trait-based analysis of structural heterogeneity in N-linked glycoproteomics data. GlycoTraitR provides a unified workflow to import GPSMs from search engine outputs, extract biologically interpretable glycan structural traits, and perform comparative analyses of micro- and macro-heterogeneity across experimental conditions using statistical testing. ImplementationThe R package and the source code of glycoTraitR are freely available on github at https://github.com/matsui-lab/glycoTraitR. A more detailed introduction and quick start guide are avaible at https://matsui-lab.github.io/glycoTraitR/.

PDFDOICode

02 /Specification & Classification

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