Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis
File(s)
Published version
Author(s)
Type
Journal Article
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 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.
Date Issued
2021-11-01
Date Acceptance
2021-09-22
Citation
Nature Methods, 2021, 18 (11), pp.1304-1316
ISSN
1548-7091
Publisher
Nature Research
Start Page
1304
End Page
1316
Journal / Book Title
Nature Methods
Volume
18
Issue
11
Copyright Statement
© The Author(s) 2021, corrected publication 2021 Open Access This 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 http://creativecommons.org/licenses/by/4.0/.
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/34725484
PII: 10.1038/s41592-021-01309-x
Subjects
ALGORITHM
Biochemical Research Methods
Biochemistry & Molecular Biology
CELL
GLYCOMICS
GLYCOSYLATION ANALYSIS
IDENTIFICATION
Life Sciences & Biomedicine
LIQUID-CHROMATOGRAPHY
MASS-SPECTROMETRY
O-GLYCOPEPTIDES
PROTEINS
Science & Technology
SIALYLGLYCOPEPTIDE
Publication Status
Published
Coverage Spatial
United States
Date Publish Online
2021-11-01