STAR ProtocolsBioinformaticsPeer-reviewed journal article
Preparing glycomics data for robust statistical analysis with GlyCompareCT
Yujie ZhangiD, Sridevi KrishnaniD, Bokan BaoiD, Austin W.T. ChiangiD, James T. SorrentinoiD, Song‐Min SchinniD, Benjamin P. KellmaniD, Nathan E. LewisiD
Abstract
SummaryGlycomics data are rapidly increasing in scale and diversity. Complexities in glycan biosynthesis (hierarchy, competition, and compartmentalization) make preprocessing critical to address resulting sparsity (many similar glycosylation profiles may share few common glycans) and non-independence (substrate-competition in glycan biosynthesis results in non-independence incompatible with many statistical methods). Here, we present GlyCompareCT, a portable command-line tool, to address these challenges thereby facilitating downstream analyses. Given glycan abundances, GlyCompareCT conducts substructure decomposition to quantify hidden biosynthetic intermediate abundance and relationships between measured glycans. Thus, GlyComparCT mitigates sparsity and makes interdependence explicit thereby increasing statistical power. Ultimately, GlyComparCT is a user-friendly implementation of substructure analysis designed to increase accessibility, interoperability, and scope and consistency in glycomics analysis. Availability and implementationSource code, test data, and instructions for GlyCompareCT v1.1.0 are available at: https://github.com/LewisLabUCSD/GlyCompareCT Supplementary informationhttps://github.com/LewisLabUCSD/GlyCompareCT/raw/main/Supplementary%20Material.pdf
- assay: metagenomics
- research focus: dimensionality reduction
- research focus: benchmarking
- research focus: software / tool
- approach: statistical model
- Citations
- 5
- FWCI
- 0.44
- Field percentile
- top 49%
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