Unified data model
Every package speaks the same tidy grammar, letting you pass glycan-rich data seamlessly through the pipeline.
The Glycoverse Ecosystem
Use a coordinated family of R packages to move from raw glyco-omics data to glycan-aware insights, faster than ever before.
Every package speaks the same tidy grammar, letting you pass glycan-rich data seamlessly through the pipeline.
Glycan topology, motifs, and enzymatic context stay connected to your quantitative measurements.
Packages can be used together or independently, suitable for any glyco-omics workflow.
Explore the workflow
Swipe through runnable examples that mirror the glyco-omics journey from raw measurements to pathway reconstruction.
# Support mainstream software
exp <- read_pglyco3("results.txt")
# Automatic preprocessing
clean_exp <- auto_clean(exp)# ANOVA
gly_anova(clean_exp)
# Limma
gly_limma(clean_exp)# Unified function API
go_res <- gly_enrich_go(clean_exp)
# Automatic visualization
autoplot(go_res)# Advanced motif analysis
motif_exp <- quantify_motifs(clean_exp, "Lewis X")
# Ready for statistical analysis
gly_kruskal(motif_exp)# Site-specific derived traits
trait_exp <- derive_traits(clean_exp)
# Again, a smooth pipeline
gly_kruskal(trait_exp)# Any glycan structure string
glycan <- "Gal(b1-3)[GlcNAc(b1-6)]GalNAc(a1-"
# Get biosynthesis insights
rebuild_biosynthesis(glycan)Meet the packages
Modular building blocks cover the journey from raw glyco-omics measurements to annotated glycan structures.
Get started with the glycoverse ecosystem in minutes with these two entry points.
Tackle glycomics data from the first import through visual communication with reproducible, shareable code.
Organize experimental context
A tidy data framework for glycoproteomics and glycomics experimental data with experiment() container.
Import diverse formats
Read quantification results from Byonic, StrucGP, pGlyco3, Glyco-Decipher, and MSFragger.
Automatic preprocessing
Preprocess glycomics data with normalization, missing value handling, and batch correction.
Model glycomic signatures
Statistical analysis including differential testing, PCA, clustering, and survival modeling.
Communicate insights
Exploratory visualizations for glycomics data with autoplot() methods.
Connect biological meaning to glycan compositions, motifs, and enzyme pathways with interoperable libraries.
Consistent representations
Computational representations of glycan compositions and structures with IUPAC support.
Interpret glycan strings
Parse IUPAC, WURCS, GlycoCT, and Linear Code into glycan structures.
Find recurring motifs
Detect glycan motifs using subgraph isomorphism with curated databases.
Detect glycan patterns
Calculate site-specific derived traits like galactosylation and sialylation.
Trace enzymatic context
Simulate glycosylation biosynthesis and map glycans to glycosyltransferases.
Annotate glycan hierarchy
Deduce glycan compositions and refine structures from mass or generic inputs.
Access glycan database
Query determined glycan structures from GlyTouCan with full linkage information.
Draw SNFG cartoons
Draw beautiful SNFG (Symbol Nomenclature for Glycans) cartoons.