Introduction
Glycoproteomics is a rapidly expanding field, but analyzing the LC-MS data remains a complex, multi-step process. In the post, Laurent emphasizes that software is a central player in scientific research. Here is his simple but powerful equation:
Experimental design + data + software = results
For glycoproteomics data, advanced search engines such as Byonic, MSFragger, pGlyco3, Glyco-Decipher, and StructGP are indispensable for identifying glycopeptides. However, identification alone is not the end of the workflow.
Researchers need downstream analytical tools to: interpret glycan structural features, quantify glycan heterogeneity, compare biological groups, and extract mechanistic insight.
To address this need, we developed glycoTraitR, an R package that extends the analysis capability to the glycoproteomics context:
Software = Software (search engine) + Software (analysis tool, e.g., glycoTraitR)
glycoTraitR is designed for users who want to go beyond simple differential analysis, extracting, summarizing, and analyzing glycan structural traits from GPSM data generated by pGlyco3 or Glyco-Decipher.
It provides a streamlined workflow for:
- parsing WURCS 2.0 and pGlyco3 glycan strings
- computing composition & structural traits
- summarizing glycan–PSM trait matrices at site/protein level (
SummarizedExperiment) - performing differential trait analysis and visualizing trait changes
Download Package
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("matsui-lab/glycoTraitR")