Package: glystats 0.10.1

glystats: Statistical Analysis of Glycoproteomics and Glycomics Data

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.

Authors:Bin Fu [aut, cre]