Using R Libraries

Many commonly used R packages are included in the base R installation available on HCC clusters, such as tidyverse and stringr. However, users are able to install other packages in their user libraries.

Adding packages

There are two options to install packages. The first is to run R on the login node and run R interactively to install packages. The second is to use the R CMD INSTALL command.

All R packages must be installed from the login node. R libraries are stored in user’s home directories which are not writable from the worker nodes.

Installing packages interactively

  1. Load the R module with the command module load R
    • Note that each version of R uses its own user libraries. To install packages under a specific version of R, specify which version by using the module load command followed by the version number. For example, to load R version 3.5, you would use the command module load R/3.5
  2. Run R interactively using the command R
  3. From within R, use the install.packages() command to install desired packages. For example, to install the package ggplot2 use the command install.packages("ggplot2")

Some R packages, require external compilers or additional libraries. If you see an error when installing your package you might need to load additional modules to make these compilers or libraries available. For more information about this, refer to the package documentation.

Installing packages using R CMD INSTALL

To install packages using R CMD INSTALL the zipped package must already be downloaded to the cluster. You can download package source using wget. Then the R CMD INSTALL command can be used when pointed to the full path of the source tar file. For example, to install ggplot2 the following commands are used:

# Download the package source:
wget https://cran.r-project.org/src/contrib/ggplot2_3.2.1.tar.gz

# Install the package:
R CMD INSTALL ./ggplot2_2.2.1.tar.gz

Additional information on using the R CMD INSTALL command can be found in the R documentation which can be seen by typing ?INSTALL within the R console.