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We encourage users to maintain their own R packages. This ensures that the user has no discontinuity in their workflow waiting for packages to be installed and that packages work with the user’s chosen, loaded R module. R packages are built specifically to a version of R and may not work properly if a different version of R is loaded. O2’s LMOD “module” feature allows users to quickly and easily switch between R versions.

Related commands:

Command Meaning
module avail R shows the versions of R installed on O2
module load R/version loads an individual module
module unload R/version unloads an individual module
which R shows the current version of R loaded
> installed.packages() from R, shows currently-installed packages

Setting up a personal R library

This sets up an environment to store R packages locally. From R, all packages will be installed and saved to this R library by default. It is recommended to use a separate R library for each version of R selected (swap Version Selected for the R chosen, like 3.2.5 or 3.3.3, etc). Multiple members of a group can share an R library saved in a group-accessible location by following the echo... and export... commands.

In O2 bash ($):

    mfk8@login02:~$ mkdir -p ~/R-VersionSelected/library
    mfk8@login02:~$ echo 'R_LIBS_USER="~/R-VersionSelected/library"' >  $HOME/.Renviron
    mfk8@login02:~$ export R_LIBS_USER="/home/user123/R-VersionSelected/library"

Starting R Interactively

R should not be executed from the login servers (login0X). Instead, launch an interactive session, specifying the memory requirements. R does not implicitly use multiple cores unless the code is parallelized, so 1 core is sufficient. Here’s a model R workflow:

	mfk8@login02:~$ srun --pty -p interactive -t 0-12:00 --mem 8000 -n 1 /bin/bash
	mfk8@compute-a-01-01:~$ module load gcc/6.2.0 R/3.2.5 #or version chosen
	mfk8@compute-a-01-01:~$ R
	> #notice how the prompt changes.

Installing Packages Using Bioconductor

The majority of bio-related packages can be downloaded through Bioconductor.

     > source("")
    > biocLite()
    > biocLite("nameofpackage")


User example:

     > source(")
    > biocLite("affy")
    > library(affy)


Bioconductor packages are listed at

Installing Packages Using CRAN

The command install.packages() searches CRAN by default and asks you to select a mirror, but a repos can be specified using this command:

     > install.packages("nameofpackage", repos="")


User example:

     > install.packages("foreign", repos="")
    > library(foreign)


A list of CRAN available packages is available at

Installing Packages from github using devtools

With the devtools package, users can install software from github repositories. First install and call library on devtools, then use the install_github() command.

	> install.packages('devtools')
	> library(devtools)
	> install_github('username/repo')

Installing Packages from Local File

If there is a package that needs to be manually downloaded (via wget/curl/etc), user should put the package in ~/R-VersionSelected/library and install it like this:

In R (>):

     > install.packages("name-of-your-package", lib="~/R-VersionSelected/library")


Conversely, if all dependencies are already existing for the package, R CMD INSTALL can be used from the command line (on an interactive compute node):

	mfk8@login02:~$ srun --pty -p interactive -t 0-12:00 --mem 8000 /bin/bash
	mfk8@compute-a-01-01:~$ module load gcc/6.2.0 R/3.2.5 #or version selected
	mfk8@compute-a-01-01:~$ R CMD INSTALL downloadedRPackage.tar.gz

Loading Packages

At the top of any script that uses an R package, the package must be explicitly called via library().

     > library("nameofpackage")


User case for a new R session, with these packages already installed:

     > library(affy)
    > library(foreign)

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