arnaumontagud/dockmaboss repository overview

⁠Description

Collection of Docker images:

• logical_pipeline is 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 code docker 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.

• PhysiBoSS is 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 code docker pull gletort/physiboss.

⁠Usage

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.