Genevieve

This project, a summer project at the GMC lab, is a remake of their GETevidence page. It utitlizes django and celery and is designed to compare .vcf files to a ClinVar database.

Installation

These instructions were written for Ubuntu Linux 13.10 or 14.04.

Clone the Git repository

Navigate to the directory you want to have the code in, and clone the repository with: git clone git://github.com/emilysa/Genevieve.

Add expected additional data files

Genevieve needs the following data to enable interpretion of Complete Genomics var files:

1. Go to the data_files/ directory
2. Add the hg19.2bit file to this directory by typing: wget http://hgdownload-test.cse.ucsc.edu/goldenPath/hg19/bigZips/hg19.2bit.

(Other ways of adding this file are fine.)

Create local, secret settings

Copy genevieve/settings_local_example.py to genevieve/settings_local.py and replace the stub variables with your own local/secret values.

Install pip, virtualenv, and virtualenvwrapper

1. (Root user action) Install pip: sudo apt-get install python-pip
2. (Root user action) Use pip to install virtualenv and virtualenvwrapper: sudo pip install virtualenv virtualenvwrapper.

Set up virtualenv and virtualenvwrapper

1. Make a directory to store your virtual environments: mkdir ~/.virtualenvs
2. To make virtualenv and virtualenvwrapper commands work in future terminals, add the following to your bashrc (or zshrc, as appropriate): export WORKON_HOME=$HOME/.virtualenvs and source /usr/local/bin/virtualenvwrapper.sh.

Make a virtual environment and install required Python packages

If you open a new terminal you should now be able to access the virtualenvwrapper commands listed below.

If you aren't familiar with pip and virtualenv: these are standard tools in Python development, greatly facilitating package management. Whenever working on this software you should do so within the virtual environment (e.g. after performing step 2 below).

1. Create a new virtual environment for working on this code: mkvirtualenv genevieve
2. Start using this virtual environment: workon genevieve
3. Navigate to top directory in this project. (One of the subdirectories should be file_process.) Install the Python packages required for development with pip install -r requirements.txt.

Set up RabbitMQ

Celery requires a message broker. This broker acts a middleman sending and receiving messages to Celery workers who in turn process tasks as they receive them. Celery recommends using RabbitMQ, an open source tool.

1. (Root user action) Install RabbitMQ: sudo apt-get install rabbitmq-server
2. Ubuntu automatically begins running a rabbit server in the background once this is installed.
3. (Root user action) Starting the server is as simple as: sudo rabbitmq-server (runs in the foreground), or you can start it in the background with sudo rabbitmq-server -detached. To stop the server use sudo rabbitmqctl stop.

Launch Celery

To launch Celery, from the project's base directory run: celery -A genevieve worker -l info (this runs in the foreground)

Initialize and run Django

In a new terminal, start your virtual environment (with workon genevieve) and run the following in the project's base directory to initialize the database and then run a local Django server.

1. python manage.py migrate
2. python manage.py runserver

If you're running this locally, you'll be able to navigate to http://127.0.0.1:8000 in a web browser. This demo will allow you to upload a file to the site, it will then asynchronously create a gzipped version of that file. Once the gzip is done, a link to the gzipped file will appear.