The Refinery Platform is a data management, analysis and visualization system for bioinformatics and computational biology applications. The platforms consists of three major components: a data repository with rich metadata capabilities, a workflow engine based on the popular Galaxy system, and visualization tools to support the exploration and interpretation of results at all stages of the analysis process.
$ git clone [email protected]:refinery-platform/refinery-platform.git
$ cd refinery-platform
$ vagrant up
The above step should take about 15 minutes depending on the speed of your machine and Internet connection. If you get an error, simply retry by:
$ vagrant provision
Open http://192.168.50.50:8000/ in your web browser.
Create a Python 2.7 virtual environment (optional but recommended, assumes virtualenvwrapper
is installed):
$ mkvirtualenv -a $(pwd) refinery-deployment
Install deployment tools (assumes header files for Python are installed):
$ pip install -r deployment/requirements.txt
Install Pre-Commit Hooks
Use fabricrc.sample
to update or initialize Fabric configuration, for example:
$ cp fabricrc.sample ~/.fabricrc
To pull the latest code and update Refinery installation:
$ fab vm update
Connect to the initialized VM:
$ vagrant ssh
$ workon refinery-platform
$ ./manage.py [command]
Log in to Refinery (http://192.168.50.50:8000/) with the default guest user account (username: guest, password: guest).
Log in to Django admin UI (http://192.168.50.50:8000/admin/) with the default superuser account (username: admin, password: refinery).
Please see installation notes for more details, including information on how to configure Galaxy for this setup.
vagrant provision
repeatedly to install all
dependencies successfully. Any errors in the output of vagrant provision
indicate that you have to re-run the command.export C_INCLUDE_PATH=/usr/local/include
vagrant reload --provision
or vagrant up --provision