Preparing glycomics data for robust statistical analysis with GlyCompareCT

GlyCompareCT is a portable command-line tool to facilitate downstream glycomic data analyses, by addressing data inherent sparsity and non-independence. Inputting glycan abundances, users can run GlyCompareCT with one line of code to obtain the abundances of a minimal substructure set, named glycomo...

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Autores principales: Zhang, Yujie, Krishnan, Sridevi, Bao, Bokan, Chiang, Austin W.T., Sorrentino, James T., Schinn, Song-Min, Kellman, Benjamin P., Lewis, Nathan E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Protocol
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10025275/
https://www.ncbi.nlm.nih.gov/pubmed/36920914
http://dx.doi.org/10.1016/j.xpro.2023.102162
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author Zhang, Yujie
Krishnan, Sridevi
Bao, Bokan
Chiang, Austin W.T.
Sorrentino, James T.
Schinn, Song-Min
Kellman, Benjamin P.
Lewis, Nathan E.
author_facet Zhang, Yujie
Krishnan, Sridevi
Bao, Bokan
Chiang, Austin W.T.
Sorrentino, James T.
Schinn, Song-Min
Kellman, Benjamin P.
Lewis, Nathan E.
author_sort Zhang, Yujie
collection PubMed
description GlyCompareCT is a portable command-line tool to facilitate downstream glycomic data analyses, by addressing data inherent sparsity and non-independence. Inputting glycan abundances, users can run GlyCompareCT with one line of code to obtain the abundances of a minimal substructure set, named glycomotif, thereby quantifying hidden biosynthetic relationships between measured glycans. Optional parameters tuning and annotation are supported for personal preference. For complete details on the use and execution of this protocol, please refer to Bao et al. (2021).(1)
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spelling pubmed-100252752023-03-21 Preparing glycomics data for robust statistical analysis with GlyCompareCT Zhang, Yujie Krishnan, Sridevi Bao, Bokan Chiang, Austin W.T. Sorrentino, James T. Schinn, Song-Min Kellman, Benjamin P. Lewis, Nathan E. STAR Protoc Protocol GlyCompareCT is a portable command-line tool to facilitate downstream glycomic data analyses, by addressing data inherent sparsity and non-independence. Inputting glycan abundances, users can run GlyCompareCT with one line of code to obtain the abundances of a minimal substructure set, named glycomotif, thereby quantifying hidden biosynthetic relationships between measured glycans. Optional parameters tuning and annotation are supported for personal preference. For complete details on the use and execution of this protocol, please refer to Bao et al. (2021).(1) Elsevier 2023-03-13 /pmc/articles/PMC10025275/ /pubmed/36920914 http://dx.doi.org/10.1016/j.xpro.2023.102162 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Zhang, Yujie
Krishnan, Sridevi
Bao, Bokan
Chiang, Austin W.T.
Sorrentino, James T.
Schinn, Song-Min
Kellman, Benjamin P.
Lewis, Nathan E.
Preparing glycomics data for robust statistical analysis with GlyCompareCT
title Preparing glycomics data for robust statistical analysis with GlyCompareCT
title_full Preparing glycomics data for robust statistical analysis with GlyCompareCT
title_fullStr Preparing glycomics data for robust statistical analysis with GlyCompareCT
title_full_unstemmed Preparing glycomics data for robust statistical analysis with GlyCompareCT
title_short Preparing glycomics data for robust statistical analysis with GlyCompareCT
title_sort preparing glycomics data for robust statistical analysis with glycomparect
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10025275/
https://www.ncbi.nlm.nih.gov/pubmed/36920914
http://dx.doi.org/10.1016/j.xpro.2023.102162
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