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

dc.creatorKawahara, Rebecca
dc.creatorChernykh, Anastasia
dc.creatorAlagesan, Kathirvel
dc.creatorBern, Marshall
dc.creatorCao, Weiqian
dc.creatorChalkley, Robert J.
dc.creatorCheng, Kai
dc.creatorChoo, Matthew S.
dc.creatorEdwards, Nathan
dc.creatorGoldman, Radoslav
dc.creatorHoffmann, Marcus
dc.creatorHu, Yingwei
dc.creatorHuang, Yifan (TTU)
dc.creatorKim, Jin Young
dc.creatorKletter, Doron
dc.creatorLiquet, Benoit
dc.creatorLiu, Mingqi
dc.creatorMechref, Yehia (TTU)
dc.creatorMeng, Bo
dc.creatorNeelamegham, Sriram
dc.creatorNguyen-Khuong, Terry
dc.creatorNilsson, Jonas
dc.creatorPap, Adam
dc.creatorPark, Gun Wook
dc.creatorParker, Benjamin L.
dc.creatorPegg, Cassandra L.
dc.creatorPenninger, Josef M.
dc.creatorPhung, Toan K.
dc.creatorPioch, Markus
dc.creatorRapp, Erdmann
dc.creatorSakalli, Enes
dc.creatorSanda, Miloslav
dc.creatorSchulz, Benjamin L.
dc.creatorScott, Nichollas E.
dc.creatorSofrononv, Georgy
dc.creatorStadlmann, Johannes
dc.creatorVakhrushev, Sergey Y.
dc.creatorWoo, Christina M.
dc.creatorWu, Hung-Yi
dc.creatorYang, Pengyuan
dc.creatorYing, Wantao
dc.creatorZhang, Hui
dc.creatorZhang, Yong
dc.creatorZhao, Jingfu (TTU)
dc.creatorZaia, Joseph
dc.creatorHaslam, Stuart M.
dc.creatorPalmisano, Giuseppe
dc.creatorYoo, Jong Shin
dc.creatorLarson, Göran
dc.creatorKhoo, Kai-Hooi
dc.creatorMedzihradszky, Katalin F.
dc.creatorKolarich, Daniel
dc.creatorPacker, Nicolle H.
dc.creatorThaysen-Andersen, Morten
dc.descriptionThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit
dc.description.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.en_US
dc.identifier.citationKawahara, R., Chernykh, A., Alagesan, K. et al. Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis. Nat Methods 18, 1304–1316 (2021).
dc.subjectComputational Platforms and Environmentsen_US
dc.subjectResearch Dataen_US
dc.titleCommunity evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysisen_US


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