Fig. 1: Study overview.

a, Two glycoproteomics data files of human serum (Files A and B) were generated and shared with participants. b, Participants comprising both developers (orange) and users (blue, team identifiers indicated) employed diverse search engines to complete the study. c, Teams returned a common reporting template capturing details of the applied search strategy including key search settings (SS1–SS13) and search output (SO1–SO9, Table 1) and their identified glycopeptides. d, Complementary performance tests (N1–N6, O1–O5; Table 2) were used to comprehensively evaluate the ability of teams to identify N- and O-glycopeptides. e, The performance profiles were used to score and rank the developers and users separately. Diverse team-wide and search engine-centric (Byonic-focused) approaches were employed to identify performance-associated variables and high-performance search strategies.