Glycans are sugar-based polymers found to modify biomolecules including lipids and proteins, as well as occur unconjugated as free polysaccharides. Due to their ubiquitous cellular presentation, glycans mediate crucial biological processes and are frequently sought after as biomarkers for a wide range of diseases. Identification of glycans present in samples acquired with mass spectrometry (MS) is a cornerstone of glycomics research, thus, the ability to rapidly identify glycans in each acquisition is integral to glycomics analysis pipelines. Here we introduce GlyCombo (https://github.com/Protea-Glycosciences/GlyCombo), an open-source, freely available software tool designed to rapidly assign monosaccharide combinations to observed and fragmented precursors in an MS experiment. GlyCombo was evaluated across six diverse datasets, demonstrating MS vendor, derivatization, and glycan-type neutrality. Compositional assignments using GlyCombo are shown to be faster than the current, predominant approach, GlycoMod, a closed-source web application. Finally, the comprehensiveness of glycan feature identification is exhibited in Skyline, a software that requires pre-defined transitions that are derived from GlyCombo output files.

Benchmarking of GlyCombo glycan identification speed and coverage compared to the current state-of-the-art GlycoMod.

N-glycans, O-glycans, and glycans released from glycosphingolipids, from a range of benchmark datasets.