In this tutorial, you will learn how to send search results from the HCA Data Explorer to Terra and how to run a basic workflow with that data.
This tutorial assumes some familiarity with the aforementioned tools. If you are not familiar with Terra, see the Overview of Terra section below.
You should also be acquainted with the content in this tutorial:
Terra recommends the Google Chrome browser, which we follow in this tutorial.
Terra is a scalable cloud platform for biomedical research. Terra offers the ability to use data, tools, and workflows to do interactive analysis in the cloud. To start using Terra, visit https://app.terra.bio.
For more information about how to use Terra, visit the Terra Support page.
To register for a Terra account, see How to register for a Terra account.
Dockstore is a platform for sharing bioscience tools by wrapping them in Docker containers and describing their use with high-level workflow languages like the Common Workflow Language (CWL) and the Workflow Description Language (WDL).
For more information about how to use the Dockstore, see the Dockstore documentation.
You can use the HCA Data Explorer to find data to export to Terra. The Data Explorer lists projects with data available for download from the Data Store and lets you filter the data for a number of attributes.
Using the Data Explorer, select some data that you are interested in. Choose anything that looks interesting - we will be running a really simple workflow that generates MD5 checksums of files, so the type of data is not important. When you have found a data set of interest, click on the big blue Export Selected Data button at the top right of the page. You will see something like this:
Click on the Export to Terra button. You will then see a page like this where you can select what kind of data to export:
Again, choose anything that looks interesting.
When you click the Request Export button, the Data Explorer will process your request, and you will be redirected to Terra.
Select a Terra workspace to import your selected data into. Once you have selected the workspace, you will see a page like this, showing the data you just exported:
Next, we find a workflow to run with the data we've just exported. For this tutorial, we are looking for dockstore-wdl-workflow-md5sum, which will generate an MD5 checksum for a file (or files) that we provide. We will need to import this workflow from Dockstore. To do that, click on the Workflows tab at the top of the page, then on the big square Find a Workflow button. It will look something like this:
Click on the Dockstore link at the bottom of the pop-up. Dockstore is a
workflow repository where we will find the workflow we want to run. Once
Dockstore has loaded, search for
md5sum. The search box is on the left
side of the page. Results should load instantly. Look for a workflow named
Once you find it, click on it. You will see this:
Note the blue Terra button at the bottom left which will let us load this workflow in Terra. Click on the button and load the workflow into your workspace. Once you have, Terra will ask you to select an input to this workflow:
On this screen, we want to select a single file from the data that we exported and find the MD5 checksum of that file. Make sure that the Process multiple workflows radio button is selected, then choose a single file to process by navigating to Select Data > Choose specific rows to process.
Next, tell the workflow how to find the file you selected by setting the inputFile variable. Click on the Attribute field (red box in the screenshot above).
Select the DRS URL attribute (something like
you're done, click Save. You will see a blue Run Analysis button pop up.
Click that one, and confirm your input when prompted. Terra's running the
workflow now - walk away for a few minutes, grab a coffee, stretch. You
When you come back, refresh the page. Hopefully, your workflow will be done running. If it is, you will seem something like this:
Note the green checkmark in the Status column.
Congrats! If you want to see the results of this workflow execution, click on the workflow ID (the UUID on the right of the page), which will show the data generated by this workflow execution.
If you would like to learn more, you might find the Jupyter notebooks in the Data Consumer Vignettes repository useful. There are several ways to run the Jupyter notebooks in that repository, including: