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 git@github.com: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.

iloveyii/cell-analysis