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

Rebeca KawaharaAnastasia ChernykhKathirvel AlagesanMarshall BernWei-Qian CaoRobert J ChalkleyKai ChengMatthew S F ChooNathan EdwardsRadoslav GoldmanMarcus HoffmannYingwei HuYifan HuangJin Young KimDoron KletterBenoit LiquetMingqi LiuYehia MechrefBo MengSriram NeelameghamTerry Nguyen-KhuongJonas NilssonAdam PapGun Wook ParkBenjamin L ParkerCassandra L PeggJosef M PenningerToan K PhungMarkus PiochErdmann RappEnes SakalliMiloslav SandaBenjamin L SchulzNichollas E ScottGeorgy SofronovJohannes StadlmannSergey Y VakhrushevChristina M WooHung-Yi WuPeng-Yuan YangWantao YingHui ZhangYong ZhangJingfu ZhaoJoseph ZaiaStuart M HaslamGiuseppe PalmisanoJong Shin YooGöran LarsonKai-Hooi KhooKatalin F MedzihradszkyDaniel KolarichNicolle H PackerMorten Thaysen-Andersen
Published in: Nature methods (2021)
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.
Keyphrases
  • data analysis
  • healthcare
  • mental health
  • electronic health record
  • big data
  • endothelial cells
  • quality improvement
  • machine learning
  • clinical practice
  • artificial intelligence
  • rna seq
  • affordable care act