Merge pull request #9 from cbg-ethz/feature/readme

feature/add_Readme

README.md

@@ -0,0 +1,87 @@
+# V-Pipe on Cloud: Front-End for On-Demand Analysis
+
+![WIP](https://img.shields.io/badge/status-WIP-yellow)
+![Python](https://img.shields.io/badge/python-3.8%2B-blue)
+![Streamlit](https://img.shields.io/badge/streamlit-0.84.0-brightgreen)
+![Docker](https://img.shields.io/badge/docker-19.03.12-blue)
+![AWS S3](https://img.shields.io/badge/AWS%20S3-Cloud-orange)
+
+This project provides a front-end interface for two primary use cases:
+- On-demand heatmaps of mutations to identify new variants emerging.
+- On-demand variant deconvolution powered by Lollipop.
+
+## Overview
+
+This front-end application is part of the "V-Pipe on Cloud" initiative, which aims to bring the capabilities of V-Pipe to the cloud, making it more accessible and scalable. The application leverages Streamlit to provide an interactive interface for users to generate heatmaps and perform variant deconvolution on-demand.
+
+For more information about V-Pipe, visit the [V-Pipe website](https://cbg-ethz.github.io/V-pipe/).
+
+## Tech Stack
+
+- **Python**: The core programming language used for the project.
+- **Streamlit**: Used for creating the front-end interface.
+- **Docker**: Used to containerize the application, ensuring consistency across different environments.
+- **AWS S3**: Used for storing and retrieving data files.
+
+## Work in Progress
+
+This project is a work in progress and is being actively developed. Contributions and feedback are welcome.
+
+## Hackathon Project
+
+This project was initiated as part of a hackathon project at the [BioHackathon Europe 2024](https://biohackathon-europe.org/).
+
+## Related Repositories
+
+This repository relates to the back-end at [vpipe-biohack24-backend](https://github.com/cbg-ethz/vpipe-biohack24-backend).
+
+## Deployment
+
+The current deployment of this project can be accessed at [biohack24.g15n.net](http://biohack24.g15n.net).
+
+## Getting Started
+
+### Prerequisites
+
+- Docker
+- AWS credentials with access to the required S3 buckets
+### Installation
+
+1. Clone the repository:
+    ```sh
+    git clone https://github.com/cbg-ethz/vpipe-biohack24-frontend.git
+    cd vpipe-biohack24-frontend
+    ```
+
+2. Build the Docker image:
+    ```sh
+    docker build -t vpipe-frontend .
+    ```
+
+3. Run the Docker container:
+    ```sh
+    docker run -p 8000:8000 --env-file .env vpipe-frontend
+    ```
+
+### Configuration
+
+1. Create a `.env` file in the root directory with your AWS credentials and S3 bucket information:
+    ```env
+    AWS_ACCESS_KEY_ID=your_access_key_id
+    AWS_SECRET_ACCESS_KEY=your_secret_access_key
+    S3_BUCKET_NAME=your_s3_bucket_name
+    ```
+
+### Usage
+
+1. Open your web browser and navigate to `http://localhost:8000` to access the application.
+
+2. Follow the on-screen instructions to upload your data and generate heatmaps or perform variant deconvolution.
+
+## Contributing
+
+Contributions are welcome! Please fork the repository and submit a pull request with your changes. For major changes, please open an issue first to discuss what you would like to change.
+
+## License
+
+This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.