Statistical Analysis of Glycoproteomics and Glycomics Data • glystats

The goal of glystats is to perform statistical analysis on glycoproteomics and glycomics data. It works seamlessly with the glyexp package.

Installation

Install glycoverse

We recommend installing the meta-package glycoverse, which includes this package and other core glycoverse packages.

Install glystats alone

If you don’t want to install all glycoverse packages, you can only install glystats.

You can install the latest release of glystats from r-universe (recommended):

# install.packages("pak")
pak::repo_add(glycoverse = "https://glycoverse.r-universe.dev")
pak::pkg_install("glystats")

Or from GitHub:

pak::pkg_install("glycoverse/glystats@*release")

Or install the development version (NOT recommended):

pak::pkg_install("glycoverse/glystats")

Note: Tips and troubleshooting for the meta-package glycoverse are also applicable here: Installation of glycoverse.

Control log transformation

All expression-analysis functions accept log_transform. Existing defaults are preserved: it is TRUE for differential tests, correlation, clustering, dimension reduction, supervised models, and set testing; it is FALSE for gly_cox(), gly_roc(), and gly_fold_change().

# Skip a second transformation when expression values are already transformed.
pca <- gly_pca(exp, log_transform = FALSE)
# Opt in for a model that previously used untransformed expression.
cox <- gly_cox(exp, log_transform = TRUE)

PCA, PLS-DA, OPLS-DA, t-SNE, and UMAP preserve log(x + 1); other analyses use log2(x + 1e-6) when enabled. Set testing uses the same choice for automatic set construction and inference. Model estimates and effect sizes reflect the selected analysis scale. Differential-test fold changes still use the original supplied values; disabling transformation does not tell these functions to back-transform already logged inputs. For limma, the existing log2fc column contains model contrasts and is only a log2 fold change when the supplied analysis scale is log2.

For gly_fold_change(), FALSE retains the log2 ratio of arithmetic group means. TRUE reports the difference of mean log2-transformed values, the log2 ratio of geometric means of x + 1e-6, rather than a ratio of logarithms. Result extraction and significance-filtering utilities do not transform expression and have no log_transform argument.

Documentation

🚀 Get started: Here
📚 Reference: Here

Role in `glycoverse`

glystats is the downstream analysis package in the glycoverse ecosystem. It provides statistical analysis functions for glyexp::GlycomicSE and glyexp::GlycoproteomicSE objects. A common workflow is to use glyread to import data, glyclean to preprocess data, and then glystats to perform statistical analysis.

Example

Say we already have a preprocessed glycomics or glycoproteomics container called exp:

# Two-sample t-test
ttest_res <- gly_ttest(exp)

# PCA analysis
pca_res <- gly_pca(exp)

# ROC analysis
roc_res <- gly_roc(exp)

That’s it! These functions use glycoverse column conventions to load needed data and perform analysis. All functions start with gly_ to leverage the auto-completion in RStudio. They accept a glyexp::GlycomicSE or glyexp::GlycoproteomicSE object, and return analysis result as a tibble or a list of tibbles. See documentation for each function for more details.

glystats