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The Need for Community Standards to Enable Accurate Comparison of Glycoproteomics Algorithm Performance.
Hackett, William E; Zaia, Joseph.
  • Hackett WE; Bioinformatics Program, Boston University, Boston, MA 02215, USA.
  • Zaia J; Bioinformatics Program, Boston University, Boston, MA 02215, USA.
Molecules ; 26(16)2021 Aug 06.
Article in English | MEDLINE | ID: covidwho-1362397
ABSTRACT
Protein glycosylation that mediates interactions among viral proteins, host receptors, and immune molecules is an important consideration for predicting viral antigenicity. Viral spike proteins, the proteins responsible for host cell invasion, are especially important to be examined. However, there is a lack of consensus within the field of glycoproteomics regarding identification strategy and false discovery rate (FDR) calculation that impedes our examinations. As a case study in the overlap between software, here as a case study, we examine recently published SARS-CoV-2 glycoprotein datasets with four glycoproteomics identification software with their recommended protocols GlycReSoft, Byonic, pGlyco2, and MSFragger-Glyco. These software use different Target-Decoy Analysis (TDA) forms to estimate FDR and have different database-oriented search methods with varying degrees of quantification capabilities. Instead of an ideal overlap between software, we observed different sets of identifications with the intersection. When clustering by glycopeptide identifications, we see higher degrees of relatedness within software than within glycosites. Taking the consensus between results yields a conservative and non-informative conclusion as we lose identifications in the desire for caution; these non-consensus identifications are often lower abundance and, therefore, more susceptible to nuanced changes. We conclude that present glycoproteomics softwares are not directly comparable, and that methods are needed to assess their overall results and FDR estimation performance. Once such tools are developed, it will be possible to improve FDR methods and quantify complex glycoproteomes with acceptable confidence, rather than potentially misleading broad strokes.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Algorithms / Glycopeptides / Glycoproteins Type of study: Prognostic study Limits: Humans Language: English Journal subject: Biology Year: 2021 Document Type: Article Affiliation country: Molecules26164757

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Algorithms / Glycopeptides / Glycoproteins Type of study: Prognostic study Limits: Humans Language: English Journal subject: Biology Year: 2021 Document Type: Article Affiliation country: Molecules26164757