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Please make sure to setup an R Personal Library on O2 to install packages locally.

Here you can find valuable information on how to install R packages requiring some external dependencies.

R package - igraph

# Load Modules
module purge
module load gcc/9.2.0 R/4.3.1 glpk/5.0

# Create ~/.R/Makevars
mkdir ~/.R
echo "CFLAGS+=-I/n/app/glpk/5.0-gcc-9.2.0/include" >> ~/.R/Makevars
echo "CPPFLAGS+=-I/n/app/glpk/5.0-gcc-9.2.0/include" >> ~/.R/Makevars
echo "LDFLAGS+=-L/n/app/glpk/5.0-gcc-9.2.0/lib" >> ~/.R/Makevars
echo "CPATH+=/n/app/glpk/5.0-gcc-9.2.0/include" >> ~/.R/Makevars

# Start R
R

# Install package
install.packages('igraph')

R package - nloptr

You must use an R version compiled against GCC v9.2.0 and load the CMake module. For example:

# Load modules
module purge
module load gcc/9.2.0 R/4.2.1 cmake/3.22.2

# Start R
R

# Install package
install.package('nloptr')

R package - Devtools

Load the git2 module if using an older R version (e.g., 4.0.1):

# Load modules
module purge
module load gcc/6.2.0 R/4.0.1 git2/1.1.0
# Start R
R

# Install pkg
install.packages('devtools')

If using the R>=4.2.1 module, then it is not required to load the git2 module.

R package - Seurat

# Load Modules
module purge
module load gcc/9.2.0 R/4.3.1

# Start R
R

# Install pkg
install.packages('Seurat')

R packages - SF and Monocle3

# Load Modules
module purge
module load gcc/9.2.0
module load cmake/3.22.2
module load R/4.3.1
module load gdal/3.1.4
module load udunits/2.2.28
module load geos/3.10.2

# Export udunits variables
export UDUNITS2_INCLUDE=/n/app/udunits/2.2.28-gcc-9.2.0/include
export UDUNITS2_LIBS=/n/app/udunits/2.2.28-gcc-9.2.0/lib

# Start R
R

# Install sf
install.packages('sf', configure.args = "--with-geos-config=/n/app/geos/3.10.2-gcc-9.2.0/bin/geos-config")

# Install Bioconductor
install.packages("BiocManager")

# Install Bioconductor pkgs
BiocManager::install(c('BiocGenerics', 'DelayedArray', 'DelayedMatrixStats',
                       'limma', 'S4Vectors', 'SingleCellExperiment',
                       'SummarizedExperiment', 'batchelor', 'Matrix.utils'))

# Install monocle3
devtools::install_github('cole-trapnell-lab/leidenbase')
devtools::install_github('cole-trapnell-lab/monocle3')

R package - ACTIONet

This package is installed within a conda environment along with a local installation of R. Unfortunately, R is needed within a conda environment to avoid clash between the suitesparse and blas libraries.

Note - Installation takes around 3 hours

# Load modules
module purge
module load conda2/4.2.13

# $PWD install the renv environment in the current directory
conda create --prefix $PWD/renv -y
source activate $PWD/renv

# Add channels
conda config --add channels bioconda
conda config --add channels conda-forge

# Install suitesparse and other depedencies
conda install -c conda-forge suitesparse -y
conda install -c conda-forge "r-essentials>=4.1" -y
conda install -c conda-forge "r-base>=4.1.2" -y
conda install -c anaconda cmake -y
conda install -c conda-forge r-hdf5r -y

# Initiate R
R

# Install R pkg devtools
install.packages("devtools")

# Install ACTIONet
# NOTE: When prompted to update the R pkgs, you must select [3] None!
devtools::install_github("shmohammadi86/ACTIONet", ref = "R-devel")

R package - InferCNV

## Install JAGS
# Setup Working Directory
cd $HOME
mkdir build_jags && cd build_jags

# Download & Decompress JAGS
wget -O JAGS-4.3.1.tgz https://sourceforge.net/projects/mcmc-jags/files/JAGS/4.x/Source/JAGS-4.3.1.tar.gz/download
tar xzvf JAGS-4.3.1.tgz && cd JAGS-4.3.1

# Load modules 
module load gcc/9.2.0 R/4.2.1

# Export Variables
export PKG_CONFIG_PATH=/n/app/openblas/0.3.19-gcc-9.2.0/lib/pkgconfig/:$PKG_CONFIG_PATH
export LDFLAGS="-L/n/app/openblas/0.3.19-gcc-9.2.0/lib/"

# Install JAGS
mkdir $HOME/JAGS
./configure --prefix=$HOME/JAGS
make -j 4
make install

# Clean up; build_jags directory is no longer needed
rm -r $HOME/build_jags

# Add JAGS path to variables 
export LD_LIBRARY_PATH=$HOME/JAGS/lib:$LD_LIBRARY_PATH
export PKG_CONFIG_PATH=$PKG_CONFIG_PATH:$HOME/JAGS/lib/pkgconfig

# Launch R
R

# Install R package
install.packages("BiocManager")
BiocManager::install("infercnv")

R package - Rmpi

The package must be installed using an sbatch job. For example:

1. Create an sbatch script with the following content

$ cat install-rmpi.slurm 
#!/bin/bash
#SBATCH -p short
#SBATCH -t 0-00:10
#SBATCH -c 1
#SBATCH --mem=1G

# load modules
module load gcc/9.2.0 R/4.2.1 openmpi/4.1.1
# install R package
R -e "install.packages('Rmpi',repos='http://cran.us.r-project.org', configure.args = '--with-mpi=/n/app/openmpi/4.1.1')"

2. Submit script via the sbatch command

$ sbatch install-rmpi.slurm