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GlypNirO: An automated workflow for quantitative N- and O-linked glycoproteomic data analysis

Mass spectrometry glycoproteomics is rapidly maturing, allowing unprecedented insights into the diversity and functions of protein glycosylation. However, quantitative glycoproteomics remains challenging. We developed GlypNirO, an automated software pipeline which integrates the complementary output...

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Detalles Bibliográficos
Autores principales: Phung, Toan K, Pegg, Cassandra L, Schulz, Benjamin L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Beilstein-Institut 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7476601/
https://www.ncbi.nlm.nih.gov/pubmed/32952729
http://dx.doi.org/10.3762/bjoc.16.180
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author Phung, Toan K
Pegg, Cassandra L
Schulz, Benjamin L
author_facet Phung, Toan K
Pegg, Cassandra L
Schulz, Benjamin L
author_sort Phung, Toan K
collection PubMed
description Mass spectrometry glycoproteomics is rapidly maturing, allowing unprecedented insights into the diversity and functions of protein glycosylation. However, quantitative glycoproteomics remains challenging. We developed GlypNirO, an automated software pipeline which integrates the complementary outputs of Byonic and Proteome Discoverer to allow high-throughput automated quantitative glycoproteomic data analysis. The output of GlypNirO is clearly structured, allowing manual interrogation, and is also appropriate for input into diverse statistical workflows. We used GlypNirO to analyse a published plasma glycoproteome dataset and identified changes in site-specific N- and O-glycosylation occupancy and structure associated with hepatocellular carcinoma as putative biomarkers of disease.
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spelling pubmed-74766012020-09-18 GlypNirO: An automated workflow for quantitative N- and O-linked glycoproteomic data analysis Phung, Toan K Pegg, Cassandra L Schulz, Benjamin L Beilstein J Org Chem Full Research Paper Mass spectrometry glycoproteomics is rapidly maturing, allowing unprecedented insights into the diversity and functions of protein glycosylation. However, quantitative glycoproteomics remains challenging. We developed GlypNirO, an automated software pipeline which integrates the complementary outputs of Byonic and Proteome Discoverer to allow high-throughput automated quantitative glycoproteomic data analysis. The output of GlypNirO is clearly structured, allowing manual interrogation, and is also appropriate for input into diverse statistical workflows. We used GlypNirO to analyse a published plasma glycoproteome dataset and identified changes in site-specific N- and O-glycosylation occupancy and structure associated with hepatocellular carcinoma as putative biomarkers of disease. Beilstein-Institut 2020-09-01 /pmc/articles/PMC7476601/ /pubmed/32952729 http://dx.doi.org/10.3762/bjoc.16.180 Text en Copyright © 2020, Phung et al. https://creativecommons.org/licenses/by/4.0https://www.beilstein-journals.org/bjoc/termsThis is an Open Access article under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0). Please note that the reuse, redistribution and reproduction in particular requires that the authors and source are credited. The license is subject to the Beilstein Journal of Organic Chemistry terms and conditions: (https://www.beilstein-journals.org/bjoc/terms)
spellingShingle Full Research Paper
Phung, Toan K
Pegg, Cassandra L
Schulz, Benjamin L
GlypNirO: An automated workflow for quantitative N- and O-linked glycoproteomic data analysis
title GlypNirO: An automated workflow for quantitative N- and O-linked glycoproteomic data analysis
title_full GlypNirO: An automated workflow for quantitative N- and O-linked glycoproteomic data analysis
title_fullStr GlypNirO: An automated workflow for quantitative N- and O-linked glycoproteomic data analysis
title_full_unstemmed GlypNirO: An automated workflow for quantitative N- and O-linked glycoproteomic data analysis
title_short GlypNirO: An automated workflow for quantitative N- and O-linked glycoproteomic data analysis
title_sort glypniro: an automated workflow for quantitative n- and o-linked glycoproteomic data analysis
topic Full Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7476601/
https://www.ncbi.nlm.nih.gov/pubmed/32952729
http://dx.doi.org/10.3762/bjoc.16.180
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