R and Rstudio

Rstudio

RStudio server is available through OnDemand as a versioned apptainer image. Each container has a slightly different configuration and availability of system libraries and pre-installed packages.

R

R is available through the module system on all the cluster nodes. To see which versions of R are available use

Terminal

module spider r

Managing Package Libraries with R and RStudio

The following will show you which paths R is using to search for packages that have been installed

R-code

.libPaths()

The order of the paths returned shows the precedence, with the first being the highest.

You can alter the paths being used with either of the following R commands

R-code

# use the specified path and fall back to other existing locations
.libPaths(c("/new/path/to/use/", .libPaths()))

# only use this path
.libPaths("/new/path/to/use/")

This method can be useful for scripts but a better and more sustainable approach is to set your library paths using either the .Rprofile or .Renviron files as described below.

.Renviron vs .Rprofile

Although both methods can configure a custom package library, they serve different purposes.

.Renviron	.Rprofile
Sets environment variables before R starts.	Executes R code after R starts.
Preferred for defining R_LIBS_USER.	Useful for calling .libPaths() or running other startup code.
Automatically works with R, Rscript, and batch jobs.	Can perform more complex configuration and conditional logic.
Simple and portable.	More flexible but also easier to misconfigure.

For most users, configuring R_LIBS_USER in .Renviron is the simplest and most robust solution.

.Renviron

The .Renviron file can be used to supply system environment variables to R. It is often used as a way of making API keys accessible within R e.g. a github API token. Bit it can also be used to set where R looks for libraries.

For a list of environmental variables that can be defined in your .Renviron file from witin R run:

R-code

?"environment variables"

To set variables for your user, use ~/.Renviron, to set variables for a RStudio project create .Renviron in the Rstudio project directory.

Create or edit your .Renviron file

Command lineWithin RStudio:

Terminal

nano ~/.Renviron

R-code

file.edit("~/.Renviron")

Set the Library Location

Add a line such as: R_LIBS_USER=/project/myproject/R/library, or alternatively, for an R-version-specific library: R_LIBS_USER=/project/myproject/R/%v, where %v is automatically replaced by the major and minor R version (for example, 4.5).

Info

Ensure you don't have any typos in the path.

It is a good idea to version stamp your library so that if you switch between different versions of R the correct packages will be used.

With R 4.5.0, the resulting library path R_LIBS_USER=/project/myproject/R/%v becomes:

/project/myproject/R/4.5

This makes it unnecessary to edit .Renviron whenever the minor R version changes.

Changes made to your .Renviron file won't take effect in an existing R or RStudio session so you will need to exit and reopen.

You can then verify the path supplied in your .Renviron file is being used with

R-code

.libPaths()

Rprofile

The .Rprofile file can be used to load specific R settings and can be set for at a user level with ~/.Rpofile or if using an R-project, at the project level by making a .Rprofile file in the project directory.

To set a custom location for installing packages, open your .Rprofile e.g. ~/.Rprofile for user level

R-code

file.edit("~/.Rprofile")

Then add the following into your .Rprofile

lib_path <- "/path/to/lib" # CHANGE THIS PATH

r_version <- paste(R.version$major,
                   strsplit(R.version$minor, "\\.")[[1]][1],
                   sep = ".")
platform <- R.version$platform
user_lib <- path.expand(sprintf("%s/R/%s-library/%s/",lib_path, platform, r_version))

if (!dir.exists(user_lib)) {
  message(sprintf("Creating user library: %s", user_lib))
  dir.create(user_lib, recursive = TRUE, showWarnings = FALSE)
}
.libPaths(c(user_lib, .libPaths()))

Warning

Make sure to edit the path in the first line

Then reload your R session and you can confirm your library path will be used with:

R-code

.libPaths()

Project level libraries with renv

If your projects have need for different package versions it would be worth looking into the renv package for managing libraries and packages at the project level - https://rstudio.github.io/renv/articles/renv.html