4.8 Article

Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis

Journal

NATURE METHODS
Volume 18, Issue 11, Pages 1304-+

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41592-021-01309-x

Keywords

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Funding

  1. Early Career Fellowship (Cancer Institute) [NSW ECF181259]
  2. Australian Research Council [FT160100344]
  3. FAPESP [2018/15549-1]
  4. Macquarie University Safety Net Grant
  5. Australian Research Council Centre of Excellence in Nanoscale Biophotonics [CE140100003]
  6. Australian Research Council [FT160100344] Funding Source: Australian Research Council

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The study evaluated the performance of glycoproteomics software, identifying high-performance informatics strategies and recommending improvements for search solutions.
Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics. This analysis presents the results of a community-based evaluation of existing software for large-scale glycopeptide data analysis.

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