iloveyii / cell-analysis

Python, Django, Cytoflow, Flowcytometry, Node, JS, Docker, PostgreSQL application for cell analysis

PC3 Cell Analysis

This is a micro services based web application for analysing the prostrate cancer cells. This application gets data from FCS file uploaded by the user and then using Flow Cytometry Tools in Python the results are shown visually on a web application.

The following tools and technologies have been used in this project.

Python	Docker

DEMO APP

Add SSH key to Github

• ssh-keygen
• cat ~/.ssh/id_rsa.pub
• Copy and paste to github

Installation

Docker

• sudo apt update
• sudo apt install apt-transport-https ca-certificates curl software-properties-common
• curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
• sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu bionic stable"
• sudo apt update
• apt-cache policy docker-ce
• sudo apt install docker-ce
• sudo systemctl status docker

Docker compose

• sudo curl -L https://github.com/docker/compose/releases/download/1.21.2/docker-compose-`uname -s-uname -m` -o /usr/local/bin/docker-compose
• sudo chmod +x /usr/local/bin/docker-compose
• docker-compose --version

Clone repo

• Clone repo git clone [email protected]:iloveyii/cell-analysis.git
• cd cell-analysis
• Pull some images from hub.docker.com

    docker pull node:8
    docker pull alikth/basic_cell:latest
    docker pull alikth/ml_cell:latest

• Run docker-compose sudo docker-compose up
• After the containers are up browse to: http://localhost

Contributions

• Two docker images prepare for this project and hosted on https://hub.docker.gom
• A Droplet purchased and deployed on Digital Ocean.
• An open source project for Cancer cell analysis using Flow Cytometry on github.