UCloud

UCloud is an HPC platform available to researchers and students at Danish universities (via a WAYF university login). It features a user-friendly graphical interface that simplifies project, user, and resource management. UCloud offers access to numerous tools via selectable apps and a variety of flexible compute resources. Check out UCloud’s extensive user docs here. For a more detailed information on navigating UCloud and using our apps, check out the Sandbox guidelines.

If you’ve chosen UCloud as your HPC platform to use the Genomics app, follow the steps below.

Step 1

Log onto UCloud at the address http://cloud.sdu.dk using university credentials.

Step 2

When logged in, choose the project from the dashboard (top-right side) from which you would like to utilize compute resources. Every user has their personal workspace (My workspace). You can also provision your own project (check with your local DeiC office if you’re new to UCloud) or you can be invited to someone else’s project. If you’ve previously selected a project, it will be launched by default. If it’s your first time, you’ll be in your workspace.

Step 3

Only for participants at the workshop

If you are participating in the GWAS workshop, you need to select Sandbox Workshop (see image below, top-right corner). This will allow us to provide a pre-configured environment with everything you need installed, along with access to our resources.

If you haven’t joined our workspace yet, please click below:

 

Invite link to UCloud workspace

 

Once you are an approved user of UCloud, you are met with a dashboard interface as below. Here you can see a summary of the workspace you are using, like the hours of computing, the storage available, and other details. The workspace you are working on is shown in the top-right corner (red circle). On the left side of the screen you have a toolbar menu.

Dashboard

Step 4

The left-side menu can be used to access the stored data, applications, running programs and settings. Use the Applications symbol (in gray). Search for the Genomics Sandbox application to open its settings.

Step 5

Choose any Job Name (#1 in the figure below), how many hours you want to use for the job (#2, choose at least 2 hours, you can increase this later), and how many CPUs (#3, choose at least 4 CPUs for the first three exercises, but use at least 8 CPUs to run the GWAS analysis). Select the Introduction to GWAS as course (#4). Then click on Submit (#5). The App needs to download data and packages which can take some time. See below how to reuse the data and avoid long waiting time (you need however to download data the first time you run the app).

Optional: select a folder from your own drive

We suggest creating a folder to store your results and any modifications you make to the notebooks. Click on Add folder. For example, work_gwas.

You will be waiting in a queue looking like this:

Step 6

As soon as there are resources, you will have them available, and in a short time the course will be ready to run. The screen you get is in the image below. Here you can increase the number of hours you want the session to run (Time allocation), close the session (Stop application) and open the interface for coding (Open interface)

Tip

Once you open the coding interface, it does not matter if you close the browser tab with the countdown timer. You can always access it again from the toolbar menu of UCloud. Simply click on Jobs and choose your session from the list of running softwares.

Now you’re ready to use JupyterLab for coding!

Note

If you have mounted your own folder, copy both the notebook and the data folder into it before running any cell.

Use the file browser on the left side to locate the Notebooks. Select one of the notebooks—it will open in the right-side panel. Carefully read the instructions and execute each code cell, starting from the first.

Make sure you have selected the correct kernel before running the cells. You’ll see the results appear directly in the notebook!

Recovering the material from your previous session

It would be annoying to start from scratch at each session, with all the analysis to be executed again. You can use data and notebooks running in a previous session of the App. Otherwise, the app will download the data and the notebooks every time. How can we avoid this?

  • A. If you copied the folder into your mounted directory, include both folders (“Add folders”) when submitting the job in future runs to maintain your own version of the notebook.

  • B. If you didn’t copy the folder, you can still access your version of the notebook. To select data from previous sessions, click “Add folders” and navigate to your latest sandbox session (inside the folder Jobs/Genomics Sandbox under your personal user folder as shown below) and select the folders you need. In this example, accepted folders are Data and Notebooks.

Download the data you generated

You can easily download files you generated by right-clicking on selected files in the browser of Jupyterlab, and by choosing download (see figure below).