Collection of Docker images:
-
logical_pipelineis a Docker image containing all scripts and tools from our logical modelling pipeline as well as all the packages that allow them to run. This image is hosted in Docker Hub and can be pulled with the following codedocker pull arnaumontagud/logical_modelling_pipeline. This image's Dockerfile has code from buildpack-deps/stretch/curl, openjdk/8-jre, rocker-org/rocker-versioned/r-ver/3.4.1 and rocker-org/rocker-versioned/rstudio/3.4.1. -
PhysiBoSSis a Docker image containing our tool PhysiBoSS that can be used to model multi-scale biological problems. This image is hosted in Docker Hub and can be pulled with the following codedocker pull gletort/physiboss.
To use the logical_pipeline docker image, it is necessary, after installing Docker, to run the following type:
docker pull arnaumontagud/logical_modelling_pipeline
Before doing anything please else, please take note of your local Docker machine's IP using:
docker-machine ip default
We recommend that you copy or clone the contents of the logical modelling pipeline GitHub repository and mount that folder on the Docker container using the -v flag when running it with the command
docker run --rm -ti -p 8787:8787 -v "/{local_tutorial_folder}":/home/rstudio/data arnaumontagud/logical_modelling_pipeline
If you do not want to mount the local folder, the image can be started with the command:
docker run --rm -ti -p 8787:8787 arnaumontagud/logical_modelling_pipeline
At this point, you will be able to use the terminal to run all the tutorial. In the parts in which you need to run R, run command
/init
This will bring an RStudio web interface containing all the necessary packages. This web interface will be availabe, in Unix-like systems, at the address http://localhost:8787 and in Windows systems at http://your-local-Docker-machine's-IP:8787. It is then possible to access the interface by using "rstudio" as the username and password.
If any problem is encountered using this RStudio image see the instructions here.
After starting the interface, it is possible to write r code as in the desktop version of RStudio.