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