This Python client provides a simple web application which fetches data from the Google Genomics API, the NCBI Genomics API or the Local Readstore through a web interface.

It can be run with app engine or without. See the docs for more information.

To run with app engine, you'll need to download and install Google App Engine SDK for Python.

On Mac OS X you can setup and run the application through the GoogleAppEngineLauncher UI. To use the command line or to run on Linux:

cd api-client-python
dev_appserver.py .

To run on Windows:

cd api-client-python
python c:\path\to\dev_appserver.py .

Once running, visit http://localhost:8080 in your browser to browse data from the API.

If you don't want to use App Engine, you can instead run the local server with paste. First you'll need to install pip.

Then install the required dependencies and run the localserver.py file:

pip install WebOb Paste webapp2 jinja2
python localserver.py

If you want to pull in data from Google Genomics API you will need to set API_KEY in main.py to a valid Google API key.

• First apply for access to the Genomics API by following the instructions at https://developers.google.com/genomics/
• Then create a project in the Google Developers Console or select an existing one.
• On the APIs & auth tab, select APIs and turn the Genomics API to ON
• On the Credentials tab, click create new key under the Public API access section.
• Select Server key in the dialog that pops up, and then click Create. (You don't need to enter anything in the text box)

• Copy the API key field value that now appears in the Public API access section into the top of main.py. It should look something like this:

  API_KEY = "abcdef12345abcdef"

Note: You can also reuse an existing API key if you have one. Just make sure the Genomics API is turned on.

• The google.appengine.tools.devappserver2.wsgi_server.BindError: Unable to bind message means that one of the default App Engine ports is unavailable. The default ports are 8080 and 8000. You can try different ports with these flags:

  python dev_appserver.py --port 12080 --admin_port=12000 .

Your server will then be available at localhost:12080.

main.py:

queries the Genomics API and handles all OAuth flows. It also serves up the HTML pages.

main.html:

is the main HTML page. It is displayed once the user has granted OAuth access to the Genomics API. It provides the basic page layout, but most of the display logic is handled in JavaScript.

static/js/main.js:

provides some JS utility functions, and calls into readgraph.js.

static/js/readgraph.js:

handles the visualization of reads. It contains the most complex code and uses d3.js to display actual Read data.

The python client also depends on several external libraries:

httplib2:

used to fetch data from API providers

D3:

is a javascript library used to make rich visualizations

Underscore.js:

is a javascript library that provides a variety of utilities

Bootstrap:

supplies a great set of default css, icons, and js helpers

In main.html, jQuery is also loaded from an external site.

• Provide an easily deployable demo that demonstrates what Genomics API interop can achieve for the community.
• Provide an example of how to use the Genomics APIs and OAuth to build a non-trivial python application.

This code wants to be in active development, but has few contributions coming in at the moment.

Currently, it provides a basic genome browser that can consume genomic data from any API provider. It deploys on App Engine (to meet the 'easily deployable' goal), and has a layman-friendly UI.

Awesome possible features include:

• Incorporating variant data into the UI.
• Add more information to the read display (show inserts, highlight mismatches against the reference, etc)
• Possibly cleaning up the js code to be more plugin friendly - so that pieces could be shared and reused (d3 library? jquery plugin?)
• Staying up to date on API changes (readset searching now has pagination, etc)
• Better searching of Snpedia (or another provider)
• Other enhancement ideas are very welcome
• (for smaller/additional tasks see the GitHub issues)