The word glycoverse has two meanings:
- The
glycoverseecosystem refers to a set of packages that together form a comprehensive pipeline for glycomics and glycoproteomics data analysis, includingglyrepr,glyexp, etc. - The
glycoversemeta-package is a meta-package that helps manage glycoverse packages (installation, update, and status check).
This repository is for the glycoverse meta-package.
Installation
Install from r-universe
You can install the latest release of glycoverse core packages from r-universe (recommended) with:
# install.packages("pak")
pak::repo_add(glycoverse = "https://glycoverse.r-universe.dev")
pak::pkg_install("glycoverse")This will install the meta-package glycoverse, as well as all glycoverse core packages, including glyexp, glyread, glyclean, glystats, glyvis, glyrepr, glyparse, glymotif, glydet, and glydraw.
Troubleshooting: If you encounter a “Failed to download xxx” or “403” error, it is likely a network issue. R-universe has strict rate limiting (or access controls). Try switching your network environment or installing directly from GitHub.
Note that you can also install packages individually:
pak::repo_add(glycoverse = "https://glycoverse.r-universe.dev") # you only need to run this once in a session
pak::pkg_install("glymotif") # this will also install glyrepr, glyparse, and glyexpInstall from GitHub
Prerequisite: To install packages from GitHub, you’ll need the proper compilation tools installed on your system. This means RTools for Windows and Xcode Command Line Tools for macOS. Without them, you’ll likely see a “Could not find tools necessary to compile a package” error. If you’re unsure about the process, a quick search for “install R package from GitHub” will provide helpful context on why these tools are necessary.
Installing from GitHub is a little tricky. Package dependencies within glycoverse are resolved assuming all packages are on r-universe (some on CRAN or Bioconductor). It means that when running the following code:
# Do NOT run:
pak::pkg_install("glycoverse/glyxxx@*release") # common practice to install a GitHub packageInstalling glyxxx from GitHub in this way does not bypass R-universe entirely, as its dependencies are still hosted there. If you are experiencing network issues with R-universe, switching to the GitHub version of glyxxx will not resolve the problem.
To truely install a glycoverse package from GitHub (along with all its dependencies), you have to install them one by one following the dependency tree:
pak::pkg_install("glyrepr") # from CRAN
pak::pkg_install("glyparse") # from CRAN
pak::pkg_install("glycoverse/glyexp@*release")
pak::pkg_install("glycoverse/glydraw@*release")
pak::pkg_install("glycoverse/glyread@*release")
pak::pkg_install("glycoverse/glyclean@*release")
pak::pkg_install("glycoverse/glystats@*release")
pak::pkg_install("glycoverse/glymotif@*release")
pak::pkg_install("glycoverse/glyvis@*release")
pak::pkg_install("glycoverse/glydet@*release")
# The meta-package
pak::pkg_install("glycoverse/glycoverse@*release")Note: Check the DESCRIPTION file of each package to find its dependencies.
Troubleshooting: Encountering an “HTTP error 403”? This usually means your IP has been rate-limited by GitHub. To resolve this, you need to configure a Personal Access Token (PAT).
- Sign up for a GitHub account.
- Install Git on your local machine.
- Generate a PAT via your GitHub settings.
- Configure the PAT locally (e.g., using the
gitcredsR package).
For a step-by-step guide, search for “How to set up GitHub PAT for R.”
Important Note
glycoverse before v0.2.5 used GitHub releases instead of r-universe releases. We recommend all users to update the meta-package glycoverse to the latest version for better package update experience.
pak::repo_add(glycoverse = "https://glycoverse.r-universe.dev")
pak::pkg_install("glycoverse")Learning glycoverse
If you want an out-of-box data analysis experience, learn glyexp and glyread, then try glysmith.
If you want to learn glycoverse systematically, first checkout one of the following case studies that showcase the basic workflow of glycoverse:
Then refer to the documentation of the individual packages for more details.
We recommend the following learning order for regular omics data analysis:
glyexp (very important) -> glyread -> glyclean -> glystats -> glyvis
If you’re dealing with glycan structures, learn these additional packages:
glyrepr (very important) -> glyparse -> glymotif -> glydet -> glydraw
You will also find glydb and glyanno very useful, if your glycan compositions or structures are in low resolution.
Usage
library(glycoverse) will load all the core packages in the glycoverse ecosystem:
library(glycoverse)
#> Warning: 程序包'glyread'是用R版本4.5.2 来建造的
#> Warning: 程序包'glyrepr'是用R版本4.5.2 来建造的
#> Warning: 程序包'glydraw'是用R版本4.5.2 来建造的
#> ── Attaching core glycoverse packages ───────────────── glycoverse 0.2.5.9000 ──
#> ✔ glyclean 0.12.1 ✔ glyparse 0.5.5
#> ✔ glydet 0.10.2 ✔ glyread 0.9.1
#> ✔ glydraw 0.3.1 ✔ glyrepr 0.10.0
#> ✔ glyexp 0.12.4 ✔ glystats 0.6.5
#> ✔ glymotif 0.13.1 ✔ glyvis 0.5.1
#> ── Conflicts ───────────────────────────────────────── glycoverse_conflicts() ──
#> ✖ glyclean::aggregate() masks stats::aggregate()
#> ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorsThis includes:
Omics data analysis
- glyexp, for data management
- glyread, for data import
- glyclean, for data cleaning and preprocessing
- glystats, for statistical analysis
- glyvis, for data visualization
Glycan structure analysis
- glyrepr, for glycan structure representation
- glyparse, for glycan structure parsing
- glymotif, for glycan structure motif analysis
- glydet, for glycan derived trait analysis
- glydraw, for glycan structure visualization
You can also install the non-core glycoverse packages if needed:
- glyenzy, for glycan biosynthesis pathway analysis
- glydb, for glycan database
- glyanno, for glycan annotation
- glysmith, for full analytical pipeline
You can get a situation report of all the packages in the glycoverse ecosystem with glycoverse_sitrep():
glycoverse_sitrep()
#> ── R & RStudio ─────────────────────────────────────────────────────────────────
#> • R: 4.5.1
#> 'getOption("repos")' replaces Bioconductor standard repositories, see
#> 'help("repositories", package = "BiocManager")' for details.
#> Replacement repositories:
#> CRAN: https://cloud.r-project.org
#> ── Core packages ───────────────────────────────────────────────────────────────
#> • glyexp (0.12.4)
#> • glyread (0.9.1)
#> • glyclean (0.12.1)
#> • glystats (0.6.5)
#> • glyvis (0.5.1)
#> • glyrepr (0.10.0 < 0.10.1)
#> • glyparse (0.5.5)
#> • glymotif (0.13.1)
#> • glydet (0.10.2)
#> • glydraw (0.3.1)
#> ── Non-core packages ───────────────────────────────────────────────────────────
#> • glyenzy (0.4.3)
#> • glydb (0.4.0)
#> • glyanno (0.1.2 < 0.2.0)
#> • glysmith (0.9.1)To list all dependencies of glycoverse core packages, run:
glycoverse_deps(recursive = TRUE) # recursive = TRUE to list dependencies of each package
#> 'getOption("repos")' replaces Bioconductor standard repositories, see
#> 'help("repositories", package = "BiocManager")' for details.
#> Replacement repositories:
#> CRAN: https://cloud.r-project.org
#> # A tibble: 127 × 5
#> package source upstream local behind
#> <chr> <chr> <chr> <chr> <lgl>
#> 1 glyclean runiverse 0.12.1 0.12.1 FALSE
#> 2 glydet runiverse 0.10.2 0.10.2 FALSE
#> 3 glydraw runiverse 0.3.1 0.3.1 FALSE
#> 4 glyexp runiverse 0.12.4 0.12.4 FALSE
#> 5 glymotif runiverse 0.13.1 0.13.1 FALSE
#> 6 glyparse runiverse 0.5.5 0.5.5 FALSE
#> 7 glyread runiverse 0.9.1 0.9.1 FALSE
#> 8 glyrepr runiverse 0.10.1 0.10.0 TRUE
#> 9 glystats runiverse 0.6.5 0.6.5 FALSE
#> 10 glyvis runiverse 0.5.1 0.5.1 FALSE
#> # ℹ 117 more rowsAnd you can update all the packages with glycoverse_update():