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Importing data

Use this command to validate a dataset in the folder ./study-dir, connecting to the web API of the container cbioportal-container, and import it into the database configured in the image, saving an html report of the validation to ~/Desktop/report.html. Note that the paths given to the -v option must be absolute paths.

docker run -it --rm --net cbio-net \
    -v "$PWD/study-dir:/study:ro" \
    -v "$HOME/Desktop:/outdir" \
    cbioportal-image \
    metaImport.py -u http://cbioportal-container:8080/cbioportal -s /study --html=/outdir/report.html

⚠️ after importing a study, remember to restart cbioportal-container to see the study in the home page. Run docker restart cbioportal-container

Using cached portal side-data

In some setups the data validation step may not have direct access to the web API, for instance when the web API is only accessible to authenticated browser sessions. You can use this command to generate a cached folder of files that the validation script can use instead:

docker run --rm --net cbio-net \
    -v "$PWD/portalinfo:/portalinfo" \
    -w /cbioportal/core/src/main/scripts \
    cbioportal-image \
    ./dumpPortalInfo.pl /portalinfo

Then, grant the validation/loading command access to this folder and tell the script it to use it instead of the API:

docker run -it --rm --net cbio-net \
    -v "$PWD/study-dir:/study:ro" \
    -v "$HOME/Desktop:/outdir" \
    -v "$PWD/portalinfo:/portalinfo:ro" \
    cbioportal-image \
    metaImport.py -p /portalinfo -s /study --html=/outdir/report.html

Importing data (method 2)

Similar to the method above, but here you open a bash shell in an otherwise idle container and run the commands there.

Step 1 (one time only for a specific image)

Set up the container importer-container mapping the input and output dirs with -v parameters, and keep it running idle in the background:

docker run -d --name="importer-container" \
  --restart=always \
  --net=cbio-net \
   -v "$PWD"/study-dir:/study:ro \
   -v "$HOME"/Desktop:/outdir \
  cbioportal-image tail -f /dev/null

Step 2

Run bash in the container and execute the import command.

docker exec -it importer-container bash

The import command:

 metaImport.py -u http://cbioportal-container:8080/cbioportal -s /study --html=/outdir/report.html

Running cBioPortal code from a local folder

If you have checked out (or modified) a git branch locally in ~/cbioportal and you want to run or debug it, you can use the following command. Note that the path given to the -v option must be an absolute path. The mapping for port 8000 and the references to JPDA open a port for remote debugging software to attach. The image is used as a runtime environment and as a cache for dependencies when compiling, while the portal.properties file will be read from the source folder.

docker run --rm \
    -p 8000:8000 \
    -p 8080:8080 \
    -v "$HOME"/cbioportal:/cbioportal \
    --net=cbio-net \
    --name=cbioportal-dev \
    cbioportal-image \
    sh -c 'mvn -DskipTests clean install && rm -f "$CATALINA_HOME/webapps/cbioportal.war" && unzip portal/target/cbioportal*.war -d "$CATALINA_HOME/webapps/cbioportal/" && JPDA_ADDRESS=0.0.0.0:8000 exec catalina.sh jpda run'

Testing cBioPortal code from a GitHub branch

If you want to run and test code from a branch you have not checked out locally, say from someone else’s pull request, you can use a command like the following. This example checks out the rc branch of the GitHub repository for thehyve.

docker run --rm \
    -p 8081:8080 \
    --net=cbio-net \
    --name=cbioportal-test \
    cbioportal-image \
    sh -c 'git fetch https://github.com/thehyve/cbioportal.git rc && git checkout FETCH_HEAD && mvn -DskipTests clean install && rm -f "$CATALINA_HOME/webapps/cbioportal.war" && unzip portal/target/cbioportal*.war -d "$CATALINA_HOME/webapps/cbioportal/" && exec catalina.sh run'

Inspecting or adjusting the database

When creating the database container, you can map a port on the local host to port 3306 of the container running the MySQL database, by adding an option such as -p 127.0.0.1:8306:3306 to the docker run command before the name of the image (mysql:5.7). You can then connect to this port (port 8306 in this example) using MySQL Workbench or another MySQL client.

If you have not opened a port, the following command can still connect a command-line client to the container (cbioDB here) using the --net option:

docker run -it --rm \
    --net=cbio-net \
    -e MYSQL_HOST=cbioDB \
    -e MYSQL_USER=cbio \
    -e MYSQL_PASSWORD=P@ssword1 \
    -e MYSQL_DATABASE=cbioportal \
    mysql:5.7 \
    sh -c 'mysql -h"$MYSQL_HOST" -u"$MYSQL_USER" -p"$MYSQL_PASSWORD" "$MYSQL_DATABASE"'