File Upload

Files can be uploaded to the platform on the workspace portal page by clicking the Upload & Export tab and then the red Upload button.

Do not upload any data that contains PII or PHI information per the Terms of Service that you agreed to as a user of the Precision Medicine Platform.

Users have the option to upload a single file or multiple files at once. More details on how to upload multiple files is found on the Multiple Files tab within the Upload dialog box.

Once the files are uploaded and you have launched your workspace, the files will be found in the folder labeled uploaded_files/notebook/ or uploaded_files/researcher_data/ on the Jupyter home page (path: /mnt/workspace/uploaded_files/).

Note: The time it takes to upload data is dependent on the internet upload speed

It is our recommendation that you Cut the files that you upload to the uploaded_files folder and Paste them into a separate folder within /mnt/workspace/ prior to unzipping or working on them. The uploaded_files folder is meant to be a temporary space to hold the files you need to get into your Workspace. From there, it is best practice to create separate folders and cut/paste your files into these new folders and to work out of those folders.

SFTP Transfer

Should you have very large data files and need SFTP set up to upload the data, please click the “Request SFTP” button.

Data and Code within a workspace can be synced with the workspace portal by moving it to the /mnt/workspace/Export_Files directory within the workspace. Files located in this directory will display under the Export Files section of workspace portal.
Note: Due to the secure nature of the workspace, certain files will not sync with the workspace portal. To extract this data, please file a ticket with Technical Support.

Data can be downloaded in the workspace in the same fashion as your personal computer. Add a new tab in Chrome, navigate to the download link, and click download.

• This will download the data in a temporary downloads folder. Simply click Upload in Jupyter or Jupyter Lab to upload the downloaded files and save them to the workspace.

Note: If you are having trouble accessing a certain link in the platform, please file a ticket with Technical Support.

Using git repositories in the workspace functions the same way as it does on a personal computer. To pull data or clone a repository, simply go to the repository in the workspace (first tab on right shown below).

• A terminal can be opened in the workspace through JupyterLab or by clicking New > Terminal in the Jupyter Home Tab
• Using login credentials or and ssh key works the same as with your personal computer.
• The example above is cloning the COVID-19 Csse_daily_reports repository from Johns Hopkins.

Tip: Make sure to access the repository in your workspace when setting up ssh keys. You cannot copy an ssh key out of the workspace

Update Workspace Name: When the workspace is provisioned, the name of the workspace is the workspace owner's User ID (which is normally their email address). To update the workspace name, click on the name and complete the form in the pop-up.

• The red Share Workspace button enables the owner to share the workspace with others, which is further detailed in the section below: The design of PMP workspaces is such that when a user is provisioned a workspace, no one except the user has access (including the AHA). All code and data is housed behind a secure walled garden that cannot be accessed by anyone other than the user. To provide workspace access for teams working on projects, the owner of a workspace can share their workspace with other people who have a PMP account.
  • Shared users can access all code and files in the workspace and it is a workspace owner's responsibility to ensure the new shared user has the appropriate data approvals prior to sharing the workspace.
  • To share a workspace with a user, click share and enter the email for the shared user on the PMP and set any desired restraints (e.g. allowing to share/publish code or allowing to start/stop the workspace)

The AHA recommends stopping your workspace when it will not be in use for a few days or longer. This preserves the overall resources needed to run and maintain a workspace and allows for updates to be completed. A workspace can be stopped by clicking the red stop button on the workspace portal. Additionally, users can change architectures and compute options when stopping and restarting. When restarting, the user will be provided the opportunity to set configurations (EMR, EC2-GPU, or EC2-CPU). For custom sizing options, please reach out to Technical Support.

Helpful Tips:

• The directory where files are located is /mnt/workspace
• The terminal can be accessed in JupyterLab or by clicking the New button in Jupyter
• The internet is available in the workspace, just click a new tab in Chrome
• To paste something inside the workspace, click the paste icon on the top menu bar. You can not copy out of the workspace due to security reasons.
• If the screen is frozen or solid blue/black, click the 4 squares on the top menu bar

Root Directory File Location

• The root path in the workspace is /mnt/workspace. This is the default directory for the Jupyter Home Page JupyterLab, R Studio and SAS Studio.

Software

• The workspace is fully customizable and other software tools not already available within the workspace are available upon request.
• R Studio, Jupyter Notebook, JupyterLab, and SAS Studio are available as tabs when a workspace is launched. The terminal and a variety of languages including R, Python, bash, and SAS can be accessed through Jupyter and JupyterLab.
• Python and R based packages can easily be installed by users via pip and install.packages respectively.
• The workspace has a Red Hat Linux Operating System. Yum can be used to get, install, and manage software installation and packages. Users are granted root access to enable customization based on user needs.
• The following software requires a log in.
• For more information and instructions on accessing and running MATLAB in your workspace, click here.
• A comprehensive list of pre-installed packages and software can be found on the About Workspaces page.
• The ReadMe notebook on the Jupyter Home page /mnt/workspace provides information regarding workspace usage, including trouble shooting instructions, software references, and tutorials.

A variety of tutorials and examples are available on the Platform. Available tutorials cover concepts such as how to load and view data, how to perform machine learning analyses with spark, how to conduct a GWAS analysis, or how to install and use software.

The ReadMe notebook on the Jupyter Home Page (/mnt/workspace) of a workspace contains an overview of the content available and the location for many of the tutorials available. Tutorials and examples can be found in the jupyter_notebooks directory (/mnt/workspace/jupyter_notebooks) of the workspace. Users can also request data science and support services for help with analyses and workspace usage. For more information, contact us.