Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis
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Published:2021-11
Issue:11
Volume:18
Page:1304-1316
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ISSN:1548-7091
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Container-title:Nature Methods
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language:en
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Short-container-title:Nat Methods
Author:
Kawahara RebecaORCID, Chernykh AnastasiaORCID, Alagesan Kathirvel, Bern MarshallORCID, Cao WeiqianORCID, Chalkley Robert J.ORCID, Cheng Kai, Choo Matthew S.ORCID, Edwards Nathan, Goldman Radoslav, Hoffmann Marcus, Hu Yingwei, Huang Yifan, Kim Jin YoungORCID, Kletter Doron, Liquet Benoit, Liu Mingqi, Mechref Yehia, Meng Bo, Neelamegham SriramORCID, Nguyen-Khuong TerryORCID, Nilsson JonasORCID, Pap Adam, Park Gun Wook, Parker Benjamin L., Pegg Cassandra L., Penninger Josef M.ORCID, Phung Toan K.ORCID, Pioch Markus, Rapp ErdmannORCID, Sakalli Enes, Sanda MiloslavORCID, Schulz Benjamin L.ORCID, Scott Nichollas E.ORCID, Sofronov GeorgyORCID, Stadlmann Johannes, Vakhrushev Sergey Y.ORCID, Woo Christina M.ORCID, Wu Hung-Yi, Yang PengyuanORCID, Ying Wantao, Zhang HuiORCID, Zhang YongORCID, Zhao Jingfu, Zaia JosephORCID, Haslam Stuart M.ORCID, Palmisano Giuseppe, Yoo Jong Shin, Larson GöranORCID, Khoo Kai-HooiORCID, Medzihradszky Katalin F., Kolarich DanielORCID, Packer Nicolle H.ORCID, Thaysen-Andersen MortenORCID
Abstract
AbstractGlycoproteomics 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 spectrometry based 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.
Publisher
Springer Science and Business Media LLC
Subject
Cell Biology,Molecular Biology,Biochemistry,Biotechnology
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