The "R" Tool is an open-source, popular, and fully-featured statistical application and programming platform. We have multiple R versions installed on HPC.
Running R on RCC Systems
To enter an interactive R session on HPC or Spear, simply "R" command. The default version that loads is Version 3.4.0. If you wish to run an older version, you must load the appropriate module before running "R"; e.g.:
# loads version 3.2.5 module load R/3.2.5 # loads version 3.2.0 module load R/3.2.0
Type 'q()' to quit R.
To submit R jobs to SLURM, refer to the following example submission script:
#!/bin/bash #SBATCH -n 1 #SBATCH -J "MyRJob" #SBATCH -p backfill #SBATCH -t 1:00:00 #SBATCH --mail-type=ALL module load R/3.2.5 R CMD BATCH yourRscript
yourRscript is a text file where you have saved R commands to run.
For more information about R, refer to the online documentation
Installing R Packages in Your Home Directory
Though RCC hosts many packages on our systems (see list below), there may be times when you need a specific package we do not currently have. In this case, you can install this package locally in your home directory using the following instructions (no need to open a ticket!):
module load R
- This will present you with the following information:
Installing package into ?/opt/hpc/R/R-3.5.2/shar/R/library? (as ?lib? is unspecified)
- You will then see a warning:
Warning in install.packages("abc") : 'lib = "/opt/hpc/R/R-3.5.2/share/R/library"' is not writable. This is normal.
- You will then be asked:
Would you like to use a personal library instead? (yes/No/cancel). Type
- You will then be asked:
Would you like to create a personal library ?~/R/x86_64-redhat-linux-gnu-library/3.5? to install packages into? (yes/No/cancel). Again, type
- You will then be shown:
--- Please select a CRAN mirror for use in this session ---
- This will bring up a list of CRAN mirrors you can use to download and install your library.
RCC has an extensive list of packages for R available.
List of Available R Packages
Bioconductor on RCC Systems
Bioconductor is a very extensive set of libraries and tools written in R for use in R programs which are designed to perform a myriad of different tasks common to bioinformatics data analysis. RCC has an extensive list of Bioconductor packages installed for use on RCC Systems. A complete list of these follows in the section below.
List of Available Bioconductor Packages
Parallel Computing with R
R has a number of powerful tools available to perform computations in parallel. This capability is vital for leveraging the full power of RCC's systems for your research. The R parallel computing tools currently supported by RCC include the following. Each has a link to their respective home pages.