ArticleCell reports methods2023
Decoding glycomics with a suite of methods for differential expression analysis.
Article in Cell reports methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Article
- The 'sugar' side of extracellular vesicle-glycome: a panorama from basic characteristics, deciphering technologies, functions, to applications.Journal of nanobiotechnology · 2026Review
- Recent advances in analytical methods and bioinformatic tools for quantitative glycomics.Analytical and bioanalytical chemistry · 2025Review
- Compositional data analysis enables statistical rigor in comparative glycomics.Nature communications · 2025Article
- Bridging worlds: connecting glycan representations with glycoinformatics via Universal Input and a canonicalized nomenclature.Bioinformatics advances · 2025Article
- O-glycosylation contributes to mammalian glycoRNA biogenesis.bioRxiv : the preprint server for biology · 2024Article
- In silico simulation of glycosylation and related pathways.Analytical and bioanalytical chemistry · 2024Review
- Syntactic sugars: crafting a regular expression framework for glycan structures.Bioinformatics advances · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Glycomics, the comprehensive profiling of all glycan structures in samples, is rapidly expanding to enable insights into physiology and disease mechanisms. However, glycan structure complexity and glycomics data interpretation present challenges, especially for differential expression analysis. Here, we present a framework for differential glycomics expression analysis. Our methodology encompasses specialized and domain-informed methods for data normalization and imputation, glycan motif extraction and quantification, differential expression analysis, motif enrichment analysis, time series analysis, and meta-analytic capabilities, synthesizing results across multiple studies. All methods are integrated into our open-source glycowork package, facilitating performant workflows and user-friendly access. We demonstrate these methods using dedicated simulations and glycomics datasets of N-, O-, lipid-linked, and free glycans. Differential expression tests here focus on human datasets and cancer vs. healthy tissue comparisons. Our rigorous approach allows for robust, reliable, and comprehensive differential expression analyses in glycomics, contributing to advancing glycomics research and its translation to clinical and diagnostic applications.
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Registered trials
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