Docker allows software to be packaged into containers: self-contained environments that contain everything needed to run the software. Containers can be run anywhere (containers run in modern Linux kernels, but can be run on Windows and Mac as well using a virtual machine called Docker Toolbox. Containers can also be deployed in the cloud using Amazon EC2 Container Service or other cloud providers.
With Bioconductor containers, we hope to enhance
Our aim is to provide up-to-date containers for the current release and devel versions of Bioconductor, and some older versions. Bioconductor’s Docker images are stored in Docker Hub; the source Dockerfiles are in Github.
Our release images are based on rocker/rstudio and built when a Biocondcutor Release occurs. Our devel images are based on rocker/rstudio-daily and built weekly with the latest versions of R and Bioconductor packages.
For each supported version of Bioconductor, we provide several images:
BiocInstaller, providing the
biocLite()function for installing additional packages). Also contains many system dependencies for Bioconductor packages. Useful when you want a relatively blank slate for testing purposes. R is accessible via the command line or via RStudio Server.
Maintained as part of the “PhenoMeNal, funded by Horizon2020 grant 654241”
The following containers are legacy and no longer updated. They have been kept to retain previous versions available via tags:
The following examples use the
Note that you may need to prepend
sudo to all
docker run -p 8787:8787 bioconductor/devel_base2
You can then open a web browser pointing to your docker host on port 8787.
If you’re on Linux and using default settings, the docker host is
localhost, so the full URL to RStudio would be
http://localhost:8787). If you are on Mac or Windows and running
Docker Toolbox, you can determine the docker host with the
docker-machine ip default command.
Log in to RStudio with the username
rstudio and password
If you want to run RStudio as a user on your host machine, in order to read/write files in a host directory, please read this.
docker run -ti bioconductor/devel_base2 R
docker run -ti bioconductor/devel_base2 bash
docker run command is very powerful and versatile.
For full documentation, type
docker run --help or visit
the help page.
There are two ways to modify these images:
The second way is the recommended way. Both ways are documented here.
These packages, plus their dependencies, are installed:
Thanks to the rocker project for providing the R/RStudio Server containers upon which ours are based.