massMatchR: a Shiny application for glycomics mass spectrometry data analysis.

Authors

Gábor Beke, Ľuboš Kľučár, Zuzana Pakanová, Rebeka Kodríkova, Peter Baráth, Marek Nemčovič

Published in

Bioinformatics (Oxford, England). Sep 22, 2026. Epub Sep 22, 2026.

Abstract

The identification and analysis of glycans using MALDI-TOF mass spectrometry is a critical task in glycomics research, yet it often requires complex data interpretation and manual processing. Existing software tools frequently lack automated solutions for efficient glycan annotation, data structuring and grouping, and semi-quantitative evaluation, making large-scale glycan analysis challenging. To address these limitations, we developed massMatchR, an open-source software tool designed to streamline the identification and quantification of glycans in MALDI-TOF spectra.
massMatchR automates glycan identification by mapping experimentally detected m/z values from preprocessed MALDI-TOF-MS datasets to glycans from a user-defined database. The software provides both visual and tabular outputs, enabling rapid and accurate glycan interpretation. Additionally, massMatchR facilitates the export of structured data tables (e.g., Microsoft Excel) with predefined fields for m/z and intensity, supporting further analysis. A key feature of the software is its ability to perform semi-quantitative evaluation based on relative intensity calculations, allowing for comparisons across multiple samples. Freely available at http://www.imb.savba.sk/soft/massMatchR/ and on GitHub implemented in R, massMatchR offers a fast, reproducible, and customizable computational framework for glycomics and MALDI-TOF -based glycan analysis.
An implementation code is available on Github at https://github.com/bekegbor/massMatchR  and on Zenodo at  https://doi.org/10.5281/zenodo.20697072.
Supplementary data are available at Bioinformatics online.

PMID:
42773703
Bibliographic data and abstract were imported from PubMed on 23 Sep 2026.

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