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Mass spectrometry is recognized as the gold standard for glycan analysis, yet the complexity of the generated data hampers progress in glycobiology, as existing tools lack full automation, requiring extensive manual effort. We introduce GlycoGenius, an open-source program offering an automated workflow for glycomics data analysis, featuring an intuitive graphical interface. With algorithms tailored to reduce manual workload, it allows for data visualization and automatically constructs search spaces, identifies, scores, and quantifies glycans, filters results, and annotates fragment spectra of N- and O-glycans, glycosaminoglycans and more. It seamlessly guides researchers of all expertise levels from raw data to publication-ready figures. Our findings demonstrate that GlycoGenius achieves results comparable to manual analysis or competing tools, identifying more glycans, including novel ones, while significantly reducing processing time. This groundbreaking tool represents a significant advancement in the study of glycoconjugates, empowering researchers to focus on insights rather than data processing.
Researchers present GlycoGenius, an open-source tool that automates complex glycomics data analysis. It streamlines workflows, identifies known and previously unreported glycans, and enables faster, more accessible insights into glycobiology.
Details
Software;
Accuracy;
Scientific visualization;
Data processing;
Data visualization;
Datasets;
Glycosaminoglycans;
Data analysis;
Source programs;
Automation;
Open source software;
User interface;
Signal transduction;
Quality standards;
Polysaccharides;
Mass spectroscopy;
Complexity;
Glycan;
Glycoconjugates
; Zheng, Jing 2 ; Ding, Yajie 2 ; Oliveira, Isadora A. 3 ; Basse, Kristoffer 2
; Todeschini, Adriane R. 4
; Horvatovich, Peter L. 2
; Lageveen-Kammeijer, Guinevere S. M. 2
1 Analytical Biochemistry, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands (ROR: https://ror.org/012p63287) (GRID: grid.4830.f) (ISNI: 0000 0004 0407 1981); Carlos Chagas Filho Biophysics’ Institute, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil (ROR: https://ror.org/03490as77) (GRID: grid.8536.8) (ISNI: 0000 0001 2294 473X); Paulo de Góes Microbiology Institute, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil (ROR: https://ror.org/03490as77) (GRID: grid.8536.8) (ISNI: 0000 0001 2294 473X)
2 Analytical Biochemistry, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands (ROR: https://ror.org/012p63287) (GRID: grid.4830.f) (ISNI: 0000 0004 0407 1981)
3 Carlos Chagas Filho Biophysics’ Institute, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil (ROR: https://ror.org/03490as77) (GRID: grid.8536.8) (ISNI: 0000 0001 2294 473X)
4 Carlos Chagas Filho Biophysics’ Institute, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil (ROR: https://ror.org/03490as77) (GRID: grid.8536.8) (ISNI: 0000 0001 2294 473X); Paulo de Góes Microbiology Institute, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil (ROR: https://ror.org/03490as77) (GRID: grid.8536.8) (ISNI: 0000 0001 2294 473X)