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On the fly variant deconvolution running in the cloud for on demand user requests.

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Lollipop on Cloud for On-Demand User Requests

WIP Python Flask Docker AWS S3

This package takes Lollipop, a tool used in V-Pipe's post-processing, and containerizes it to be run on-demand. This is part of the effort "V-Pipe on Cloud".

Overview

Lollipop is a powerful tool used in V-Pipe's post-processing pipeline. This project aims to containerize Lollipop, allowing it to be run on-demand via a Flask-based API. This enables users to perform deconvolution tasks on-demand, leveraging the power of cloud computing.

V-Pipe on Cloud

This project 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.

For more information about V-Pipe, visit the V-Pipe website.

Tech Stack

  • Python: The core programming language used for the project.
  • Flask: A lightweight WSGI web application framework used to create the web server.
  • 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.

Related Repositories

This repository relates to the front-end at vpipe-biohack24-frontend.

Deployment

The current deployment of this project can be accessed at biohack24.g15n.net.

Getting Started

Prerequisites

  • Docker
  • AWS credentials with access to the required S3 buckets

Installation

  1. Clone the repository:

    git clone https://github.com/cbg-ethz/lollipop-in-cloud.git
    cd lollipop-in-cloud
  2. Build the Docker image:

    docker build -t lollipop-in-cloud .
  3. Run the Docker container:

    docker run --env-file .env -p 8000:8000 lollipop-in-cloud
  4. Access the API: The API will be running at http://localhost:8000.

Configuration

Ensure you have a .env file, see .env.example.

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On the fly variant deconvolution running in the cloud for on demand user requests.

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