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Subsequent identification of the resulting glycopeptides by searching against database often introduces assignment errors due to similar mass differences between different permutations of amino acids and glycosyl residues. By manually interpreting the individual MS<jats:sup>2<\/jats:sup> spectra, we report here the common sources of errors in assignment, especially those introduced by the use of chymotrypsin. We show that by applying a stringent threshold of acceptance, erroneous assignment by the commonly used Byonic software can be controlled within 15%, which can be reduced further if only those also confidently identified by a different search engine, pGlyco3, were considered. A representative site\u2010specific <jats:italic>N<\/jats:italic>\u2010glycosylation pattern could be constructed based on quantifying only the overlapping subset of <jats:italic>N<\/jats:italic>\u2010glycopeptides identified at higher confidence. Applying the two complimentary glycoproteomic software in a concerted data analysis workflow, we found and confirmed that glycosylation at several sites of an unstable Omicron spike protein differed significantly from those of the stable trimeric product of the parental D614G variant.<\/jats:p>","DOI":"10.1002\/pmic.202300143","type":"journal-article","created":{"date-parts":[[2023,6,6]],"date-time":"2023-06-06T12:45:45Z","timestamp":1686055545000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["An <i>N<\/i>\u2010glycopeptide MS\/MS data analysis workflow leveraging two complementary glycoproteomic software tools for more confident identification and assignments"],"prefix":"10.1002","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4388-5748","authenticated-orcid":false,"given":"Chu\u2010Wei","family":"Kuo","sequence":"first","affiliation":[{"name":"Institute of Biological Chemistry Academia Sinica  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