R on ARC

General

Text mode interactive shell

When you start R usual way you get into interactive R shell where you can type commands and get the results back. Like this:

$ module load R/3.6.2
$ R

R version 3.6.2 (2019-12-12) -- "Dark and Stormy Night"
Copyright (C) 2019 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
....
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> Sys.info()
                              sysname                               release 
                              "Linux"              "3.10.0-1127.el7.x86_64" 
                              version                              nodename 
"#1 SMP Tue Mar 31 23:36:51 UTC 2020"                                 "arc" 
                              machine                                 login 
                             "x86_64"                            "drozmano" 
                                 user                        effective_user 
                           "drozmano"                            "drozmano" 

> quit()
$

Running R scripts from the command line

In order to run R scripts / programs on ARC as jobs you have to pre-record the commands you want in a text file, for example test.R, and run it as a script non-interactively.

test.R:

cwd = getwd()
cat(" Current Directory: ", cwd, "\n")

t = Sys.time()
cat("      Current time: ", format(t), "\n")

u = Sys.info()["user"]
cat("         User name: ", u, "\n")

There are three ways to run an R script.

From standard input

An R script can be sent to the standard input of the R interactive shell. This is similar to typing the commands in R:

$ R --no-save < test.R

R version 3.6.2 (2019-12-12) -- "Dark and Stormy Night"
Copyright (C) 2019 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

  Natural language support but running in an English locale

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> cwd = getwd()
> cat(" Current Directory: ", cwd, "\n")
 Current Directory:  /global/software/src/r/tests 
> 
> t = Sys.time()
> cat("      Current time: ", format(t), "\n")
      Current time:  2020-05-07 15:16:12 
> 
> u = Sys.info()["user"]
> cat("         User name: ", u, "\n")
         User name:  drozmano 
> 
> 

After executing all the commands from the script, R terminates. Note that both the commands and the printed output are shown.

Using CMD BATCH command

An R script can be passed as an argument to the "R CMD BATCH" command. The output does not go to the screen, but is saved to the .Rout file:

$ R CMD BATCH test.R

$ ls -l
-rw-r--r-- 1 drozmano drozmano  176 May  7 15:03 test.R
-rw-r--r-- 1 drozmano drozmano 1121 May  7 15:19 test.Rout

To see the output use the cat or less commands:

$ cat test.Rout

R version 3.6.2 (2019-12-12) -- "Dark and Stormy Night"
Copyright (C) 2019 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

  Natural language support but running in an English locale

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> cwd = getwd()
> cat(" Current Directory: ", cwd, "\n")
 Current Directory:  /global/software/src/r/tests 
> 
> t = Sys.time()
> cat("      Current time: ", format(t), "\n")
      Current time:  2020-05-07 15:19:07 
> 
> u = Sys.info()["user"]
> cat("         User name: ", u, "\n")
         User name:  drozmano 
> 
> 
> proc.time()
   user  system elapsed 
  0.219   0.079   0.369 

The output if very similar to the first way, but contains some additional timing information. Again, both the commands and the output are shown.

Using Rscript version of R

Probably the best non-interactive way to run an R script is to use a special non-interactive version of R, Rscript:

$ Rscript test.R
 Current Directory:  /global/software/src/r/tests 
      Current time:  2020-05-07 15:22:17 
         User name:  drozmano 

In this case R does not print any extra information, and only explicitly printed values are shown in the output, the commands themselves are not printed.

Using R on ARC

Like other calculations on ARC systems, R scripts and programs are run by submitting an appropriate script for batch scheduling using the sbatch command. For more information about submitting jobs, see Running jobs article.

R modules

Currently there are several software modules on ARC that provide different versions of R. The versions differ in the release date.

You can see them using the module command:

$ module avail R

----------- /global/software/Modules/3.2.10/modulefiles ---------
R/3.5.3 
R/3.6.2

In addition,

• Module biobuilds/2017.11 provides R v.3.4.2.
• Module bioconda/2018.11 provides R v.3.4.1.

These modules are designed with bioinformatics applications in mind and have a number of specialized R packages preinstalled.

Installed R packages

When installing a new R version, the following packages are typically installed at the same time.

arules          purrr           xaringan        glue            covr            lintr                   
reprex          reticulate      utf8            promises        devtools        cluster         
dbscan          epiR            epitools        glasso          Hmisc           irr             
mi              RSQLite         foreign         openxlsx        dplyr           tidyr           
stringr         stringi         lubridate       ggplot2         ggvis           rgl             
htmlwidgets     googleVis       car             lme4            nlme            mgcv    
randomForest    multcomp        vcd             glmnet          survival        caret           
shiny           rmarkdown       xtable          sp              maptools        maps            
ggmap           zoo             xts             quantmod        Rcpp            data.table              
XML             jsonlite        httr            RcppArmadillo   manipulate      proto           
dichromat       reshape2        mice            rpart           party           caret           
randomForest    nnet            e1071           kernlab         neuralnet       rnn             
h2o             RSNNS           tensorflow      keras           infer           janitor         
DataExplorer    sparklyr        drake           DALEX           raster          gpclib           

# BioConductor 
BiocManager
GenomicFeatures
AnnotationDbi
DESeq
DESeq2
MAST
FEM
DEGseq
EBSeq
DRIMSeq
SGSeqRNASeqR

If you want to use a specific R package with a centrally installed R you can check if it has already been installed before attempting installing it:

$ module load R/3.6.2 

$ R
R version 3.6.2 (2019-12-12) -- "Dark and Stormy Night"
....
Type 'q()' to quit R.

> is.installed <- function(mypkg)is.element(mypkg, installed.packages()[,1])

> is.installed("FEM")
[1] TRUE

> is.installed("e1071")
[1] TRUE

> is.installed("rgdal")
[1] FALSE

Adding R packages

Generally, we cannot support and manage specific packages for every user on our cluster. When a new version of R is installed we try to add some of the more popular packages to the install right away (see above for the list of expected packages), but if you need something outside of that list you will have to install the needed packages yourself.

Fortunately, R is very good at it and once you try to install anything yourself, R will try to save the new package to the central location, where the R files are, but it will realize that you have no rights to write to that location and will automatically create your own personal storage location inside your home directory and will save all the needed files there. Very convenient.

You only have to install the package you want once. Some R scripts or examples include installation commands (install.packages(...)) in the script body. This will cause the installation to be done every time this script runs. It is a VERY BAD idea to do on a cluster. The installation has to be done once from R's command line interpreter on the login node. There should not be any installation commands in the R script itself.

Installing a native R package

We can install the "utf8" package like this:

$ module load R/3.5.3 

$ R
R version 3.5.3 (2019-03-11) -- "Great Truth"
Copyright (C) 2019 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
....
Type 'q()' to quit R.

> is.installed <- function(mypkg)is.element(mypkg, installed.packages()[,1])
> is.installed("utf8")
[1] FALSE

> install.packages("utf8")
--- Please select a CRAN mirror for use in this session ---
Secure CRAN mirrors 

 1: 0-Cloud [https]
 2: Australia (Canberra) [https]
 3: Australia (Melbourne 1) [https]
.....
60: Uruguay [https]
61: (other mirrors)

Selection: 61
Other CRAN mirrors 

 1: Algeria [https]                2: Argentina (La Plata)        
 3: Belgium (Antwerp) [https]      4: Canada (BC) [https]         
 5: Canada (MB) [https]            6: Canada (NS) [https]         
....
35: USA (NC)                      36: USA (PA 1)                  
37: USA (PA 2)                    

Selection: 4

trying URL 'https://mirror.rcg.sfu.ca/mirror/CRAN/src/contrib/utf8_1.1.4.tar.gz'
Content type 'application/x-gzip' length 218882 bytes (213 KB)
==================================================
downloaded 213 KB

* installing *source* package ‘utf8’ ...
.....
.....
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded
* DONE (utf8)

The downloaded source packages are in
	‘/tmp/RtmpEbfZKU/downloaded_packages’
Updating HTML index of packages in '.Library'
Making 'packages.html' ... done
>
> library(utf8)
> quit()
Save workspace image? [y/n/c]: n

$

Now we can use the "utf8" package. Success. Next time you use R the package will be already there.

Some notes about the example above:

• Before installing the package we, first, have checked whether it is installed, first, by defining a is.installed() function and using it.

Even if the package is installed and available, if you ask R to install a package it will not warn you that the package is already installed.

• This example uses a CRAN mirror from Canada/BC instead a mirror from the more popular list.

Installing a wrapper package

Similar to the native package install, but when you try installing it, the install may fail, like this:

......
> is.installed <- function(mypkg)is.element(mypkg, installed.packages()[,1])

> is.installed("rgdal")
[1] FALSE

> is.installed("rgl")
[1] FALSE

> install.packages("rgdal")

--- Please select a CRAN mirror for use in this session ---
Secure CRAN mirrors 
....
Selection: 61
.....
Selection: 4

trying URL 'https://mirror.rcg.sfu.ca/mirror/CRAN/src/contrib/rgdal_1.5-10.tar.gz'
Content type 'application/x-gzip' length 2300923 bytes (2.2 MB)
==================================================
downloaded 2.2 MB

* installing *source* package ‘rgdal’ ...
** package ‘rgdal’ successfully unpacked and MD5 sums checked
configure: R_HOME: /global/software/r/r-3.5.3/lib64/R
configure: CC: gcc -std=gnu99
configure: CXX: g++
configure: CXX11 is: g++, CXX11STD is: -std=gnu++11
configure: CXX is: g++ -std=gnu++11
configure: C++11 support available
configure: rgdal: 1.5-10
checking for /usr/bin/svnversion... yes
configure: svn revision: 1006
checking for gdal-config... no
no
configure: error: gdal-config not found or not executable.
ERROR: configuration failed for package ‘rgdal’
* removing ‘/global/software/r/r-3.5.3/lib64/R/library/rgdal’

The downloaded source packages are in
	‘/tmp/RtmpGB34Hw/downloaded_packages’
Updating HTML index of packages in '.Library'
Making 'packages.html' ... done
Warning message:
In install.packages("rgdal") :
  installation of package ‘rgdal’ had non-zero exit status
>

Here you have to carefully read the output and find the reason for the failure. The key information is where the ERROR happens the first time. Here:

configure: svn revision: 1006
checking for gdal-config... no
no
configure: error: gdal-config not found or not executable.
ERROR: configuration failed for package ‘rgdal’
...

The key phrase is

 
configure: error: gdal-config not found or not executable.

The rgdal package is not a native package for R, it is not implemented from scratch for R, but instead provides a way to use a completely independent library GDAL from R environment. Therefore, the package while being installed checks for the presence of the library in the system and will only install if the library is present.

In this case, the installer could not find a piece of the GDAL library called gdal-config and aborted, assuming that the library is not present.

To install this package, first, the corresponding library has to be made available. It is possible, that the library is already installed on the cluster, but its module has to be loaded first. Like this:

$ module load R/3.5.3
$ module load osgeo/gdal/3.0.2
$ R
....
> install.packages(rgdal)
.....
.....
configure: svn revision: 1006
checking for gdal-config... /global/software/gdal/gdal-3.0.2/bin/gdal-config
checking gdal-config usability... yes
configure: GDAL: 3.0.2
....
....
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded
* DONE (rgdal)

The downloaded source packages are in
	‘/tmp/Rtmpd2nm4U/downloaded_packages’
Updating HTML index of packages in '.Library'
Making 'packages.html' ... done
>

This time the installation has been successful. The installer could find the gdal-config piece and could continue.

The package is not ready to be used in your R scripts, but every time you submit a job that is going to use it, you will have to load the corresponding osgeo/gdal/3.0.2 module before running the script.

If there is no module for the library you want to use from R, it has to be installed first. This, however, has nothing to do with R and is a completely different task.

BioConductor

Contains lots of bioinformatics related packages for R.

• Installation: https://www.bioconductor.org/install/

The BioConductor package manager should be already installed in centrally installed R versions.

Adding BioConductor packages is a bit different than installing a standard R package:

# Find packages:
> BiocManager::available()

# install specific packages:
> BiocManager::install(c("GenomicFeatures", "AnnotationDbi"))

> BiocManager::install(c("DESeq", "DESeq2"))

> BiocManager::install(c("MAST", "FEM", "DEGseq", "EBSeq", "DRIMSeq", "SGSeq", "RNASeqR"))

If you are managing your own version of R in your home directory, you can install the core part of BioConductor as follows:

> install.packages("BiocManager")
> BiocManager::install()

Then follow the instructions given above.