GlycoTraitR: an R package for characterizing structural heterogeneity in N-linked glycoproteomics data
Zhang, B.; Himori, K.; Matsui, Y.
Show 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/.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Improved open modification searching via unified spectral search with predicted libraries and enhanced vector representations in ANN-SoLo 94%
- LM-GlycoRepo Version 1.0: A novel repository system for mouse tissue glycome mapping data 94%
- Efficient indexing of peptides for database search using Tide 94%
Similar papers in this journal
- Bridging Worlds: Connecting Glycan Representations with Glycoinformatics via Universal Input and a Canonicalized Nomenclature 95%
- Syntactic Sugars: Crafting a Regular Expression Framework for Glycan Structures 94%
- Covariate balanced allocation of samples to batches to mitigate the impacts of technical variability. 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.