In this tutorial, you will learn how to create and run a notebook in JupyterLab on the platform, download data from the notebook, and upload results to the platform.

Run a JupyterLab Session and Create Notebooks

1. Run DXJupyterLab and view the project

First, launch DXJupyterLab in the project of your choice, as described in the Running DxJupyterLab guide.

Once your JupyterLab session is running, click on the DNAnexus tab on the left sidebar to see all the files and folders in the project.

2. Create an empty notebook

To create a new empty notebook in the DNAnexus project, select DNAnexus > New Notebook from the top menu.

An untitled ipynb file will be created and viewable in the DNAnexus project browser, which refreshes every few seconds.

You can rename your file by right-clicking on its name and selecting Rename.

3. Edit and save the notebook in the project

You can open and edit the newly created notebook directly from the project (accessible from the DNAnexus tab in the left sidebar). To save your changes, simply hit Ctrl/Command + S or click on the save icon in the Toolbar (an area just below the tab bar at the top). A new notebook version will land in the project, and you should see in the "Last modified" column that the file was created recently.

Since DNAnexus files are immutable, whenever you save the notebook, the current version is uploaded to the project and replaces the previous version, i.e. the file of the same name. The previous version is moved to the .Notebook_archive with a timestamp suffix added to its name. Saving notebooks directly in the project as new files ensures that your analyses won't be lost when the DXJupyterLab session ends.

4. Download the data to the execution environment

To process your data in the notebook, the data must be available in the execution environment (as is the case with any DNAnexus app).

You can download input data from a project for your notebook using dx download in a notebook cell:

%%bash
dx download input_data/reads.fastq

You can also use the terminal to execute the dx command.

5. Upload data to the project

If your notebook generates any data you'd like to keep, you should upload it to the project before the session ends, i.e. before the worker in which the JupyterLab runs is terminated. You can do it directly in the notebook by running dx upload from a notebook cell or from the terminal:

%%bash
dx upload results.csv

NOTE: If you create a notebook from the Launcher or from the top menu (File > New > Notebook), the notebook will not be created in the project but in the local execution environment. In order to move it to the project, you will have to upload it to the project manually. Make sure you upload your local notebooks to the project before the session expires, or work on your notebooks directly from the project, so as not to lose your work.

Next steps

• Check the References guide for tips on the most useful operations and features in the DNAnexus JupyterLab.