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Docker/Singularity Containers

Authors: Brian Schilder, Alan Murphy, Nathan Skene

Vignette updated: Sep-21-2024

Installation

rworkflows is now available via ghcr.io as a containerised environment with Rstudio and all necessary dependencies pre-installed.

Method 1: via Docker

First, install Docker if you have not already.

Create an image of the Docker container in command line:

docker pull ghcr.io/neurogenomics/rworkflows

Once the image has been created, you can launch it with:

docker run \
  -d \
  -e ROOT=true \
  -e PASSWORD="<your_password>" \
  -v ~/Desktop:/Desktop \
  -v /Volumes:/Volumes \
  -p 8900:8787 \
  ghcr.io/neurogenomics/rworkflows

NOTES

Make sure to replace <your_password> above with whatever you want your password to be.
Change the paths supplied to the -v flags for your particular use case.
The -d ensures the container will run in “detached” mode, which means it will persist even after you’ve closed your command line session.
The username will be “rstudio” by default.
Optionally, you can also install the Docker Desktop to easily manage your containers.

Method 2: via Singularity

If you are using a system that does not allow Docker (as is the case for many institutional computing clusters), you can instead install Docker images via Singularity.

singularity pull docker://ghcr.io/neurogenomics/rworkflows

For troubleshooting, see the Singularity documentation.

Usage

Finally, launch the containerised Rstudio by entering the following URL in any web browser: http://localhost:8900/

Session Info

utils::sessionInfo()

## R version 4.4.1 (2024-06-14)
## Platform: aarch64-apple-darwin20
## Running under: macOS Sonoma 14.6.1
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRblas.0.dylib 
## LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.0
## 
## locale:
## [1] C/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
## 
## time zone: Europe/London
## tzcode source: internal
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] data.table_1.16.0 rworkflows_1.0.2 
## 
## loaded via a namespace (and not attached):
##  [1] gtable_0.3.5        jsonlite_1.8.9      renv_1.0.8         
##  [4] dplyr_1.1.4         compiler_4.4.1      BiocManager_1.30.25
##  [7] tidyselect_1.2.1    jquerylib_0.1.4     rvcheck_0.2.1      
## [10] scales_1.3.0        yaml_2.3.10         fastmap_1.2.0      
## [13] here_1.0.1          ggplot2_3.5.1       R6_2.5.1           
## [16] generics_0.1.3      knitr_1.48          yulab.utils_0.1.7  
## [19] tibble_3.2.1        desc_1.4.3          dlstats_0.1.7      
## [22] rprojroot_2.0.4     munsell_0.5.1       bslib_0.8.0        
## [25] pillar_1.9.0        RColorBrewer_1.1-3  rlang_1.1.4        
## [28] utf8_1.2.4          cachem_1.1.0        badger_0.2.4       
## [31] xfun_0.47           fs_1.6.4            sass_0.4.9         
## [34] cli_3.6.3           magrittr_2.0.3      digest_0.6.37      
## [37] grid_4.4.1          lifecycle_1.0.4     vctrs_0.6.5        
## [40] evaluate_1.0.0      glue_1.7.0          fansi_1.0.6        
## [43] colorspace_2.1-1    rmarkdown_2.28      tools_4.4.1        
## [46] pkgconfig_2.0.3     htmltools_0.5.8.1

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.