https://glycoverse.r-universe.devRecent package updates in glycoverseR-universehttps://github.com/glycoverse.pnghttps://glycoverse.r-universe.devWed, 03 Jun 2026 05:56:07 GMT23110220018@m.fudan.edu.cn (Bin Fu)Provides a comprehensive database of glycan structures from GlyTouCan, including fully determined glycan structures with complete linkage, substituent, anomer, and monosaccharide information. This database serves as a foundational resource for the glycoverse ecosystem, enabling glycan structure analysis, comparison, and research applications.https://github.com/r-universe/glycoverse/actions/runs/26873228116Wed, 03 Jun 2026 05:56:07 GMTglydb0.5.0successhttps://glycoverse.r-universe.devhttps://github.com/glycoverse/glydb23110220018@m.fudan.edu.cn (Bin Fu)Simulates the biosynthetic process of glycosylation in silico, enabling computational analysis of glycan biosynthesis pathways. Key features include: identifying specific glycosyltransferases responsible for each glycosidic bond at the bond level; reconstructing complete biosynthetic pathways for given glycans; exploring possible transformations between two glycan structures via glycosyltransferases and glycosidases; and predicting glycans that can be synthesized from substrate structures and enzyme sets. The package supports multiple glycan types including N-glycans, O-GalNAc, O-Man, O-GlcNAc, O-Fuc, and O-Glc. As a downstream component of the glycoverse ecosystem, it integrates seamlessly with 'glyrepr', 'glyparse', and 'glymotif' to provide practical, analysis-ready insights into glycan biosynthesis for omics researchers.https://github.com/r-universe/glycoverse/actions/runs/26768842005Mon, 01 Jun 2026 10:55:54 GMTglyenzy0.5.0successhttps://glycoverse.r-universe.devhttps://github.com/glycoverse/glyenzyglyenzy.Rmdglyenzy.htmlGet Started with glyenzy2025-08-15 08:25:312026-05-31 08:32:371225774778@qq.com (Xisong Feng)Draw beautiful SNFG cartoons.https://github.com/r-universe/glycoverse/actions/runs/26456724787Tue, 26 May 2026 09:52:07 GMTglydraw0.4.1successhttps://glycoverse.r-universe.devhttps://github.com/glycoverse/glydraw23110220018@m.fudan.edu.cn (Bin Fu)The 'glycoverse' is a set of packages that together form a comprehensive pipeline for glycomics and glycoproteomics data analysis. This package is designed to make it easy to install and load multiple 'glycoverse' packages in a single step.https://github.com/r-universe/glycoverse/actions/runs/26457369331Thu, 21 May 2026 08:05:27 GMTglycoverse0.3.1successhttps://glycoverse.r-universe.devhttps://github.com/glycoverse/glycoversecase-study-2.Rmdcase-study-2.htmlCase Study: Glycomics2025-09-17 02:25:472026-05-20 03:28:17case-study-1.Rmdcase-study-1.htmlCase Study: Glycoproteomics2025-09-15 05:06:042026-05-20 03:28:1723110220018@m.fudan.edu.cn (Bin Fu)Provides a unified toolbox for bioinformatics analyses of glycomics and glycoproteomics data. Implemented methods include differential testing (t-test, Wilcoxon rank-sum test, ANOVA, Kruskal–Wallis), multivariate modeling and visualization (PCA, t-SNE, UMAP), supervised learning (PLS-DA, OPLS-DA), clustering (k-means, hierarchical, consensus clustering), network analysis (weighted gene co-expression network analysis, WGCNA), survival modeling (Cox proportional hazards), enrichment analysis, correlation analysis, and ROC/AUC evaluation. All user-facing functions follow the gly_*() naming convention to facilitate auto-completion in RStudio. The package is designed to work seamlessly with 'glyexp' and tidy data workflows.https://github.com/r-universe/glycoverse/actions/runs/26282160726Wed, 20 May 2026 02:31:07 GMTglystats0.10.1successhttps://glycoverse.r-universe.devhttps://github.com/glycoverse/glystatsglystats.Rmdglystats.htmlGetting Started with glystats2025-07-24 06:43:172026-03-29 02:15:2523110220018@m.fudan.edu.cn (Bin Fu)Provides comprehensive data preprocessing tools for glycomics and glycoproteomics experiments. The package offers both automated and manual preprocessing pipelines, including normalization (median, quantile, vsn, total area), missing value handling (filtering, imputation using various methods), batch effect correction (using ComBat and other methods), data aggregation (at peptide, glycan, or site level), and quality control functions. The automated pipeline intelligently selects appropriate methods based on data characteristics and sample size, making it easy to prepare clean, analysis-ready data for downstream statistical analysis within the glycoverse ecosystem. Works seamlessly with 'glyexp::experiment()' objects to ensure data consistency and interoperability.https://github.com/r-universe/glycoverse/actions/runs/26018346045Mon, 18 May 2026 02:52:54 GMTglyclean0.14.1successhttps://glycoverse.r-universe.devhttps://github.com/glycoverse/glycleanglyclean.Rmdglyclean.htmlGet Started with glyclean2025-06-17 15:20:392026-05-05 02:41:2623110220018@m.fudan.edu.cn (Bin Fu)Provides comprehensive tools for glycan motif analysis and detection in glycobioinformatics research. The package enables users to identify, count, and match glycan motifs (recurring substructures) within complex glycan structures using advanced subgraph isomorphism algorithms. It includes a curated database of known motifs from the GlycoMotif GlyGen Collection, supports both concrete and generic monosaccharide matching, and offers flexible alignment options (core, terminal, or anywhere). Key functionalities include motif presence detection, occurrence counting, detailed node-to-node mapping, and batch analysis of multiple glycans against multiple motifs. The package seamlessly integrates with the glycoverse ecosystem, particularly 'glyrepr' and 'glyparse', making it essential for structural glycomics analysis, biomarker discovery, and understanding glycan-mediated biological processes.https://github.com/r-universe/glycoverse/actions/runs/26457371721Sun, 17 May 2026 02:12:25 GMTglymotif0.14.1successhttps://glycoverse.r-universe.devhttps://github.com/glycoverse/glymotifglymotif.Rmdglymotif.htmlGetting Started with glymotif2025-06-17 03:49:342026-05-12 14:13:47motif-matching.Rmdmotif-matching.htmlThe Science Behind Motif Matching2025-06-22 06:18:302026-05-12 14:13:47with-exp.Rmdwith-exp.htmlWorking with glyexp2025-07-08 12:31:462026-05-12 14:13:4723110220018@m.fudan.edu.cn (Bin Fu)Computational representations of glycan compositions and structures, including details such as linkages, anomers, and substituents. Supports varying levels of monosaccharide specificity (e.g., "Hex" or "Gal") and ambiguous linkages. Provides robust parsing and generation of IUPAC-condensed structure strings. Optimized for vectorized operations on glycan structures, with efficient handling of duplications. As the cornerstone of the glycoverse ecosystem, this package delivers the foundational data structures that power glycomics and glycoproteomics analysis workflows.https://github.com/r-universe/glycoverse/actions/runs/25868577258Thu, 14 May 2026 10:12:56 GMTglyrepr0.12.0successhttps://glycoverse.r-universe.devhttps://github.com/glycoverse/glyreprsmap.Rmdsmap.htmlEfficient Glycan Manipulation with smap2025-06-15 10:28:062026-04-26 07:20:21glyrepr.Rmdglyrepr.htmlGetting Started with glyrepr2025-06-15 08:26:542026-04-26 07:07:26glycan-graph.Rmdglycan-graph.htmlGlycan Graphs: The Network Behind Glycan Structures2025-06-26 02:38:452026-04-26 07:20:2123110220018@m.fudan.edu.cn (Bin Fu)glysmith provides high-level, end-to-end workflows for glycomics and glycoproteomics data analysis within the glycoverse ecosystem. It acts as an orchestrator that integrates data cleaning, quality control, derived trait computation, motif detection, statistical testing, and visualization into unified, one-command analytical pipelines. Featuring AI-assisted pipeline generation, glysmith can intelligently translate natural language research questions into executable analysis blueprints, streamlining complex bioinformatics workflows. Built on top of the experiment() data container and domain-knowledge-aware infrastructure provided by glyclean, glydet, glymotif, glystats, glyvis, and related packages, glysmith enables users to quickly forge polished tables, figures, and analysis reports suitable for publication. The package is designed for reproducibility and ease of use, allowing both novice and advanced users to obtain standardized and structure-aware results with minimal code while retaining full flexibility for customization.https://github.com/r-universe/glycoverse/actions/runs/25538906221Fri, 08 May 2026 03:21:48 GMTglysmith0.11.0successhttps://glycoverse.r-universe.devhttps://github.com/glycoverse/glysmithai.Rmdai.htmlAI-Powered Workflow in Glysmith2026-01-04 07:05:002026-04-29 02:54:52blueprint.Rmdblueprint.htmlCustom Blueprint2026-02-27 05:42:332026-04-28 10:18:50glysmith.Rmdglysmith.htmlGet Started with glysmith2025-12-21 07:18:282026-05-07 11:41:5123110220018@m.fudan.edu.cn (Bin Fu)Calculate and analyze glycosylation derived traits for site-specific glycoproteomics data. Derived traits are summary features that aggregate individual glycan abundances into biologically meaningful groups (e.g., galactosylation, sialylation, fucosylation, branching). This package provides functions to compute well-established derived traits from the literature, and features a domain-specific language for defining custom derived traits tailored to specific research needs.https://github.com/r-universe/glycoverse/actions/runs/25979387807Mon, 04 May 2026 03:36:51 GMTglydet0.11.0successhttps://glycoverse.r-universe.devhttps://github.com/glycoverse/glydetcustom-traits.Rmdcustom-traits.htmlDefining Custom Traits2025-09-09 02:24:092026-05-03 14:30:50glydet.Rmdglydet.htmlGet Started with glydet2025-09-08 12:16:522026-05-03 14:30:50quantify-motifs.Rmdquantify-motifs.htmlQuantifying Glycan Motifs2025-10-06 06:41:362026-05-01 15:43:4123110220018@m.fudan.edu.cn (Bin Fu)Provides a unified interface for reading and processing quantification results from various glycomics and glycoproteomics software tools, including Byonic (ByoLogic, pGlycoQuant), StrucGP, pGlyco3 (pGlycoQuant), Glyco-Decipher, GlyHunter, and MSFragger. The package standardizes raw data from different sources, performs peptide-spectrum match (PSM) aggregation, parses glycan compositions and structures, and converts the data into a standardized experiment object from the 'glyexp' package for downstream analysis within the glycoverse ecosystem.https://github.com/r-universe/glycoverse/actions/runs/25869106374Sat, 02 May 2026 14:41:49 GMTglyread0.11.0successhttps://glycoverse.r-universe.devhttps://github.com/glycoverse/glyreadglyread.Rmdglyread.htmlGet Started with glyread2025-07-12 14:09:242026-02-08 06:49:1023110220018@m.fudan.edu.cn (Bin Fu)Provides a unified interface for visualizing glycomics data within the 'glycoverse' ecosystem. Implements 'autoplot()' methods for various data structures including statistical results from 'glystats', experimental data from 'glyexp', and glycan structures from 'glyrepr'. Designed for rapid data exploration and quality assessment rather than publication-quality figure generation.https://github.com/r-universe/glycoverse/actions/runs/26709231123Fri, 01 May 2026 03:58:36 GMTglyvis0.6.0successhttps://glycoverse.r-universe.devhttps://github.com/glycoverse/glyvisglyvis.Rmdglyvis.htmlGet Started with glyvis2025-09-18 04:24:362025-09-18 04:24:3623110220018@m.fudan.edu.cn (Bin Fu)Hierarchical annotation of glycans based on molecule mass, composition, and structure. Starting from a molecule mass, glyanno calculates possible glycan compositions. Given a glycan composition, glyanno further deduces possible glycan structures. For glycan structures with generic monosaccharides (e.g., "Hex", "HexNAc"), glyanno refines them into specific types (e.g., "Glc", "Gal"). For structures lacking linkage information (e.g., "Gal(??-?)GalNAc(??-"), glyanno infers the most likely linkages (e.g., "Gal(b1-3)GalNAc(a1-").https://github.com/r-universe/glycoverse/actions/runs/26873617716Thu, 30 Apr 2026 10:20:45 GMTglyanno0.5.0successhttps://glycoverse.r-universe.devhttps://github.com/glycoverse/glyannoglyanno.Rmdglyanno.htmlGet Started with glyanno2025-11-23 11:29:352026-04-26 12:06:4723110220018@m.fudan.edu.cn (Bin Fu)Provides functions to parse glycan structure text representations into 'glyrepr' glycan structures. Currently, it supports StrucGP-style, pGlyco-style, IUPAC-condensed, IUPAC-extended, IUPAC-short, WURCS, Linear Code, and GlycoCT format. It also provides an automatic parser to detect the format and parse the structure string.https://github.com/r-universe/glycoverse/actions/runs/25869105086Wed, 29 Apr 2026 05:49:58 GMTglyparse0.6.0successhttps://glycoverse.r-universe.devhttps://github.com/glycoverse/glyparseglyparse.Rmdglyparse.htmlGetting Started with glyparse2025-06-27 06:49:462025-09-24 01:28:1923110220018@m.fudan.edu.cn (Bin Fu)Provides functional enrichment analysis for glycoproteomics data, including both protein-centric and glycan-centric approaches. The 'enrich_xxx()' functions answer "Which functions are enriched for proteins with dysregulated glycosylation?" (traditional protein-level enrichment), while 'enrich_gc_xxx()' functions answer "Which functions are enriched for dysregulated glycan traits?" (glycan-centric, linking glycan traits like core-fucosylation with functional annotations). Supports both Over Representation Analysis (ORA) and Gene Set Enrichment Analysis (GSEA) with common databases including GO, KEGG, Reactome, WikiPathways, DO (Disease Ontology), and NCG (Network of Cancer Genes). Integrates seamlessly with 'glydet' (for site-specific derived traits) and 'glystats' (for differential expression analysis).https://github.com/r-universe/glycoverse/actions/runs/26139241680Sat, 25 Apr 2026 05:50:12 GMTglyfun0.1.0successhttps://glycoverse.r-universe.devhttps://github.com/glycoverse/glyfunglyfun.Rmdglyfun.htmlGet Started with glyfun2026-04-25 04:19:352026-04-25 04:19:3523110220018@m.fudan.edu.cn (Bin Fu)Provides a tidy data framework for managing glycoproteomics and glycomics experimental data. The core feature is the 'experiment()' class, which serves as a unified data container integrating expression matrices, variable information (proteins, peptides, glycan compositions, etc.), and sample metadata (groups, batches, clinical variables, etc.). The package enforces data consistency, validates column types according to experiment types (glycomics, glycoproteomics, traitomics, traitproteomics), and provides dplyr-style data manipulation functions (filter, mutate, select, arrange, slice, join) for seamless data wrangling. As the data core of the 'glycoverse' ecosystem, it provides a consistent interface that other packages can reliably extract information from, enabling smooth data exchange and analysis workflows.https://github.com/r-universe/glycoverse/actions/runs/25869101939Sun, 29 Mar 2026 02:11:08 GMTglyexp0.14.1successhttps://glycoverse.r-universe.devhttps://github.com/glycoverse/glyexpcreate-exp.Rmdcreate-exp.htmlCreating Experiments2025-09-23 04:41:532026-01-31 04:17:48dplyr-style-functions.Rmddplyr-style-functions.htmldplyr-Style Functions: Data Harmony in Action2025-06-18 09:44:452026-01-31 04:17:48exp-type.Rmdexp-type.htmlExperiment Types2025-09-21 09:28:472026-01-31 04:17:48glyexp.Rmdglyexp.htmlGet Started with glyexp2025-06-16 02:56:092026-01-31 04:17:48