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社区对糖蛋白质组学信息学解决方案的评估揭示了用于血清糖肽分析的高性能搜索策略。

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

机构信息

Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia.

Institute for Glycomics, Griffith University Gold Coast Campus, Southport, QLD, Australia.

出版信息

Nat Methods. 2021 Nov;18(11):1304-1316. doi: 10.1038/s41592-021-01309-x. Epub 2021 Nov 1.

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.

摘要

糖蛋白质组学是一种强大但具有分析挑战性的研究工具。已经出现了辅助解释复杂糖肽串联质谱的软件包,但它们的相对性能仍未经测试。这项通过 HUPO 人类糖蛋白质组学倡议进行的社区研究,包括糖蛋白质组学软件的开发人员和用户,评估了用于系统范围糖肽分析的解决方案。来自人血清的相同基于质谱的糖蛋白质组学数据集与参与者共享,通过正交性能测试全面建立了 N- 和 O-糖肽数据分析的相对团队性能。尽管结果各不相同,但确定了几种高性能糖蛋白质组学信息学策略。对数据的深入分析揭示了与性能相关的关键搜索参数,并为改进“高覆盖”和“高精度”糖蛋白质组学搜索解决方案提出了建议。这项研究得出的结论是,存在用于全面糖肽数据分析的多种软件包,指出了几种高性能搜索策略,并指定了将指导未来软件开发和协助糖蛋白质组学信息学决策的关键变量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bb41/8566223/e0c3815c6c37/41592_2021_1309_Fig1_HTML.jpg

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