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

糖蛋白质组学信息学解决方案的社区评估揭示了血清糖肽分析的高性能搜索策略

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作者:Rebeca Kawahara, Anastasia Chernykh, Kathirvel Alagesan, Marshall Bern, Weiqian Cao, Robert J Chalkley, Kai Cheng, Matthew S Choo, Nathan Edwards, Radoslav Goldman, Marcus Hoffmann, Yingwei Hu, Yifan Huang, Jin Young Kim, Doron Kletter, Benoit Liquet, Mingqi Liu, Yehia Mechref, Bo Meng, Sriram Neela

Abstract

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.

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