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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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Bibliographic Details
Published in:STAR protocols 2023-06, Vol.4 (2), p.102162, Article 102162
Main Authors: Zhang, Yujie, Krishnan, Sridevi, Bao, Bokan, Chiang, Austin W.T., Sorrentino, James T., Schinn, Song-Min, Kellman, Benjamin P., Lewis, Nathan E.
Format: Article
Language:English
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Summary: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 [Display omitted] •Bioinformatics tool for processing glycomic data sets•Glycan structure decomposition to increase statistical power and increase interpretability•Easy-to-use command line executables Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. 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.
ISSN:2666-1667
2666-1667
DOI:10.1016/j.xpro.2023.102162