ARROW

Allele-specific Recombined sgRNA design for Reduced Off-target With computational profiling

Quick Start

This application runs within Docker containers. Ensure you have Docker installed before proceeding.

1. Download the Application

• Download the source code for running the application. You can clone the GitHub repository using the following command:

  git clone https://github.com/dwchoo/ARROW.git
  cd ARROW

• If you only want to download the docker-compose file, please run the command below.

  wget https://raw.githubusercontent.com/dwchoo/ARROW/refs/heads/main/docker-compose.yml
  # If you do not have an Nvidia GPU, you must run it using the CPU version below.
  # wget https://raw.githubusercontent.com/dwchoo/ARROW/refs/heads/main/docker-compose.cpu.yml

2. Run the Application: Navigate to the directory containing the docker-compose.yml file and execute the following command:

   docker compose up -d
   # If you do not have an Nvidia GPU, you must run it using the CPU version command below.
   # docker compose -f docker-compose.cpu.yml up -d

3. Access the Application: Once the containers are running, open your web browser and go to http://localhost:38080.

Note: This Quick Start uses the default configuration, which is optimized for GPU environments.

Usage

Uploading FASTA Files

YouTube link

Managing Jobs

YouTube link

Docker Compose Configuration Details

The docker-compose.yml file defines how the application is run within Docker. Here's a breakdown of the key options:

• runtime: nvidia: This option enables the use of an NVIDIA GPU for accelerated processing. If you don't have an NVIDIA GPU, you should use the CPU version.
• volumes:
  • - ./gen-ref:/gen_ref: This mounts the gen-ref directory on your computer to the /gen_ref directory inside the container. This is where the application expects to find reference files needed for the analysis. You should place your reference files in the ./gen-ref directory.
• environment: These are environment variables that configure the application within the container:
  • REF_DIR=/gen_ref: This variable tells the application where to find the reference files inside the container (which is /gen_ref).
  • RESULTS_DIR=/results_dir: This variable specifies where the application should store the results of the analysis inside the container.
  • GMAIL_ID=False and GMAIL_PW=False: These variables are used for email notifications. Setting them to False disables email notifications. If you want to enable email notifications, you should replace False with your Gmail ID and password. (Do not change it,does not work.)
  • DJANGO_SUPERUSER_EMAIL=xxx@email.com: This sets the email address for the Django superuser account. You should change xxx@email.com to your email address. (Do not change it,does not work.)
  • DJANGO_SUPERUSER_USERNAME=admin: This sets the username for the Django superuser account.
  • DJANGO_SUPERUSER_PASSWORD=Arrow: This sets the password for the Django superuser account. You should change this to a more secure password.
  • TIME_ZONE=UTC: This sets the timezone inside the container to Coordinated Universal Time (UTC).
  • NVIDIA_VISIBLE_DEVICES=0: This specifies that the application should use the first available NVIDIA GPU (device 0).
  • NVIDIA_DRIVER_CAPABILITIES=compute,utility: This option specifies the capabilities of the NVIDIA driver that the container needs.
• ports:
  • - 38080:8080: This maps port 38080 on your computer to port 8080 inside the container. This is how you access the web application in your browser at http://localhost:38080.

Installation and Execution

This application can be easily installed and run using Docker. Follow the steps below to get started.

1. Install Docker

To run the application, you must first have Docker installed. If you don't have Docker installed, download and install Docker Desktop for your operating system from the following link:

• Download Docker

2. Download the Application

Download the source code for running the application. You can clone the GitHub repository using the following command:

git clone https://github.com/dwchoo/ARROW.git
cd ARROW

3. Build the Docker Image

Build the Docker image required to run the application. Execute the following command in the directory containing the docker-compose.yml file:

docker compose build

This command will build a new image based on the ghcr.io/dwchoo/arrow:latest image, as defined in the docker-compose.yml file. The build process may take some time depending on your internet connection.

4. Run the Application

Once the Docker image has been built successfully, you can run the application using the following command:

docker compose up -d

The -d option runs the application in detached mode (in the background).

5. Access the Application

If the application runs successfully, you can access it by opening your web browser and navigating to the following address: http://localhost:38080

6. Stop the Application

To stop the application, execute the following command in the directory containing the docker-compose.yml file:

docker compose down
# CPU version
# docker compose -f docker-compose-cpu.yml down

This command will stop and remove the running containers.