Installation

Step 1: Install Docker

Before using the provided Dockerfile, ensure Docker is installed on your system. Follow the official instructions based on your operating system:

Docker Installation Guide
Ensure Docker is properly installed by running the following command in your terminal:

docker --version

Step 2: Clone the GitHub Repository

Clone the repository containing the Dockerfile to your local machine. Replace with the actual URL of your repository:

git clone https://github.com/Moldia/PLP_directRNA_design_V2.git
cd PLP_directRNA_design_V2

Step 3: Build the Docker Image

Build the Docker image using the docker build command. Replace with a name of your choice for the image:

docker build -t plp_probe_design_v2 .

Running the docker image

Step 1: Run the Docker Container

After successfully building the image, create and run a container using the following command:

docker run -it --rm -p 2222:2222 plp_probe_design_v2

Step 2: Checking installation of required tools (blat & cutadapt)

You can test whether blat is installed just running the tool without any parameters which print the help:

blat 

You can test whether cutadapt is installed:

cutadapt --version

Step 3: Start Jupyter Notebook from Within the Container

After entering the container's shell, start the Jupyter Notebook with the following command:

jupyter notebook --ip=0.0.0.0 --port=2222 --no-browser --allow-root

Then in your browser open this address: http://localhost:2222

Mounting data to Docker Container

You should mount the data and relevant files (e.g. jupyter notebooks)

docker run -it -p 2222:2222 \
  -v /home/nima/Lee_2023/nima_dataset/:/app \
  -v /home/nima/PLP_directRNA_design_V2/codes/Benchmarking.ipynb:/app/Benchmarking.ipynb  \
  plp_probe_design_v2

Any changes you make to the mounted files or directories inside the container will be reflected in the original files on your host system.