GDAP - Gene-Disease Association Prediction App

[Docs] [Streamlit App]

Requirements

To install and run the project, you will need:

• Python 3.11+: Ensure you have Python 3.11 or higher installed. You can download it from python.org.
• uv: Fast Python package installer and resolver. Install it from uv.dev.
• Dependencies: The project requires the Python packages listed in pyproject.toml and locked in uv.lock.

Quick Start

The easiest way to get started is using the provided Makefile:

# Install dependencies
make install

# Run the Streamlit app
make run-app

# Run the main script
make run-script

How to install

1. Clone the Repository from terminal:

   git clone https://github.com/mentorchains/BI-ML_Disease-Prediction_2024.git
   cd BI-ML_Disease-Prediction_2024

2. Install Dependencies using uv:

   # Install production dependencies
   make install
   
   # Or install with development tools
   make install-dev

How to Run the Script

1. Go to Open Target Platform and obtain the disease EFO ID.

2. Update the configuration in config.py for your experiment. If you choose BigQuery as a data source, ensure you set up your GOOGLE_APPLICATION_CREDENTIALS and follow the steps to obtain the necessary JSON key files.

3. From the project root, run the script:

   # Using Makefile (recommended)
   make run-script
   
   # Or using uv directly
   uv run python src/main.py

How to Run the App

Running Locally

1. Run the following command from the project root:

   # Using Makefile (recommended)
   make run-app
   
   # Or using streamlit directly
   streamlit run streamlit_app.py

Running the App via Docker

To run the app using Docker, follow these steps:

1. Build and run the Docker container:

   # Using Makefile (recommended)
   make run-app-docker
   
   # Or manually
   docker build -t gdap .
   docker run -p 8501:8501 gdap

Available Make Commands

# Installation
make install
make install-dev

# Development
make fix
make test
make lint
make format

# Running Applications
make run-script
make run-app

# Docker
make run-app-docker
make run-app-docker-dev

# Cleanup
make clean
make clean-docker
make clean-docker-all

# Help
make help

Repo's directory structure

The directory structure below shows the nature of files/directories used in this repo.

GDAP/
├── streamlit_app.py        <- Main Streamlit entry point for deployment
├── requirements.txt        <- Dependencies for Streamlit Cloud
├── app/                    <- Streamlit applications
├── src/                    <- Source code
│   ├── gdap/               <- Main package
│   ├── config.py           <- Configuration
│   └── main.py             <- Main script
├── data/                   <- Data files
├── docs/                   <- Documentation
├── notebook/               <- Jupyter notebooks
├── tests/                  <- Test files
├── pyproject.toml          <- Project config
└── Makefile                <- Build commands

Team Structure and Contribution

@ahmedsalim3

References

Provide references of repositories, articles, other work used by your teams.

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