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Run iPython Notebooks on Compute Engine

The properly rendered version of this document can be found at Read The Docs.

If you are reading this on github, you should instead click here.

`Google Cloud Datalab`_ is built on Jupyter (formerly IPython) and enables analysis of your data in `Google BigQuery`_, `Google Compute Engine`_, `Google Cloud Storage`_, and `Google Genomics`_ using Python, SQL, and JavaScript (for BigQuery user-defined functions).

Read Example Notebooks

There are several example notebooks for genomics use cases upon public data such as the :doc:`/use_cases/discover_public_data/platinum_genomes`, :doc:`/use_cases/discover_public_data/1000_genomes`, and :doc:`/use_cases/discover_public_data/isb_cgc_data`. You can read them on github:

Run Notebooks

To run the examples yourself:

  1. Launch your own Cloud Datalab instance in the cloud or run it locally.
  2. Work through the introductory notebooks that are pre-installed on Cloud Datalab.
  3. Run git clone on your local file system to download the notebooks.
  4. Import the genomics notebooks into your Cloud Datalab instance by navigating to the notebook list page and uploading them.

If you are running in the cloud, be sure to shut down Cloud Datalab when you are no longer using it. Shut down instructions and other tips are here.