Exporting REDCap Data into R

1. Get a REDCap account for a project URL and API key

2. Go to

3. Click “New Application” and choose Blackbalsam Clinical

4. Click on “black balsam” folder and then click on RedCapAPIRDemo.ipynb

5. In the notebook, on cell 2 substitute REDCap URL and API key with your credentials

6. Run first three cells in the notebook

7. To export records, use show_forms, show_fields, or show_all_records cells

Using the restartr notebook to get data into mongodb

1. Go to and login.

2. Click on “New Application”, choose Blackbalsam Clinical then click "Create Application".

3. Click on the "blackbalsam" directory and then launch the RestartrApiDemo.ipynb notebook.

4. In cells 3 to 6 substitute your api-key here "<put-api-key>".

5. Run the first two cells in the notebook.

• The first cell imports the required dependencies.

• The second cell is where data can be formatted to insert into mongodb.

6. Run the third cell to persist data into mongodb.

• This cell will call the observation api and insert data into mongodb.

• Upon a successful call it will return an id, for example {"id": "\"5f355dd39e55e62921768dec\""}.

7. To query the data use, query by "_id", query by sub-field, or just use query methods provided in the RestartrApiDemo.ipynb notebook.

Testing the CloudTop Docker

Step 1: Run the CloudTop Docker.

USER_NAME and VNC_PW can be whatever you want: those are the authentication info you will need to log in for Step 2. Change the tag to whichever tag you want to test.

Step 2: Connect to the running docker

• Browse to localhost:8080

• Enter the USERNAME and VNC_PW you specified when starting the Dockerfile

Step 3: Make sure the home directory is OK

• Start a terminal emulator from the applications menu. In the resultant shell, type

• You should see /home/USER_NAME where USER_NAME is the user name specified in Step 1

• Note the presence of the Firefox browser icon

At this point the basic CloudTop functionality is working.

Testing the CloudTop OHIF Docker

Step 1: Run the CloudTop OHIF docker:

where OUR_CLIENT_ID is found in the file.

google_health.env file in the renci_data_stage directory of our keybase account. USER_NAME and VNC_PW can be whatever you want: those are the authentication info you will need to log in for Step 2. Change the tag to whichever tag you want to test.

Step 2: Connect to the running docker

• Browse to localhost:8080

• Enter the USERNAME and VNC_PW you specified when starting the Dockerfile

Step 3: Make sure the home directory is OK

• Start a terminal emulator from the applications menu. In the resultant shell, type:

• You should see /home/USER_NAME where USER_NAME is the user name specified in Step 1

• Note the presence of the Firefox browser icon

At this point the basic CloudTop functionality is working.

Step 4: Test the OHIF functionality

• Exit the terminal emulator by typing “exit”

• Click the Firefox icon and browse to localhost:3000

• At this point you will be prompted for your Google user ID.

Step 5: Browse to Your Data Set

• Select helx-dev

• Select the northamerica- northeast1 region

• Select the DicomTestData dataset

Testing the CloudTop ImageJ/Napari Docker

Step 1: Start the Docker

• Start the docker with the following command:

where USER_NAME and VNC_PW can be whatever you want: those are the authentication info you will need to log in for Step 2. Change the tag to whichever tag you want to test.

Step 2: Connect to the running docker

• Browse to localhost:8080

• Enter the USERNAME VNC_PWyou specified when starting the Dockerfile

Step 3: Make sure the home directory is OK

• Start a terminal emulator from the applications menu. In the resultant shell, type:

• You should see /home/USER_NAME where USER_NAME is the user name specified in Step 1

• Note the presence of the ImageJ, Napari and Firefox browser icon. If any are missing the test fails.

At this point the basic CloudTop functionality is working. Next we will want to verify that ImageJ and Napari are working

Step 4: Make sure the ImageJ application launcher works correct

• Exit the terminal application and click the ImageJ icon. There is no ImageJ test data included in the docker.

• Exit ImageJ and make sure the Napari application launcher works correctly.

• The docker does not contain any test data. The docker test is now complete.

Introduction

Jupyter/datascience includes popular packages for data analysis from the Python, Julia and R communities and also packages are included from its ancestor images jupyter/sci-py notebook, jupyter/r-notebook and jupyter/minimal-notebook.

Some of the packages it includes are,

, , , , , , , , , , , , , , , , , , , , , , , and packages

and for interactive visualizations and plots in Python notebooks.

for visualizing machine learning datasets.

The compiler and base environment.

to support Julia code in Jupyter notebooks.

, , and packages.

Working with jupyter-datascience notebook in HeLx

Step-1:

Launch a jupyter-datascience notebook from HeLx by clicking on “Launch Application” button.

Step-2:

This brings us to the jupyter-lab panel where we can select the environment that we want to work on (Python, Julia, R).

Step-3:

Start working on it. Below code shows loading iris dataset (features, labels) from sklearn package to train/test our machine learning model.

Running the DICOM Viewer Application

Step 1: Connect to the application

• Enter the USERNAME and VNC_PW you have been provided

• Press the Login button

• Wait for the app to respond

Step 2: Use OHIF functionality

• Click the Firefox icon and browse to localhost:3000

• At this point you will be prompted for your Google user ID.

• Click Next.

Step 3: Browse to The example Data Set

• Select helx-dev

• Select the northamerica- northeast1 region

• Select the DicomTestData dataset

Coming soon.

Introduction

Nextflow enables scalable and reproducible scientific workflows using software containers. It allows the adaptation of pipelines written in the most common scripting languages.

Its fluent DSL simplifies the implementation and the deployment of complex parallel and reactive workflows on clouds and clusters.

Working with Nextflow on HeLx

Step-1:

Launch a Nextflow API by clicking on the "New Application" button on the app manager page on HelX.

Step-2:

This brings us to the Nextflow API home page, where we can view the launched workflows and create new workflows.

Step-3:

Below is a demo of how to launch a systemsgenetics/kinc workflow. Click on "Create Workflow" button and fill in the form to give it a "Name" and specify the Pipeline (in this case systemsgenetics/kinc-nf).

Step-4:

Uploading the necessary files, a GEM file in the format "*.emx.txt" and a nextflow.config file(can upload all files at once). Click on "Upload" button.

Step-5:

Now we are all set to launch the workflow. Go ahead and click on "Launch" button. This should show all the logs of the processes/jobs running in the background on the Kubernetes cluster.

Coming soon.