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 passed to the -v
option must be
absolute paths.
docker run -it --rm --net cbio-net \
-v /<path_to_config_file>/portal.properties:/cbioportal/portal.properties:ro \
-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
cbioportal-container
to see the study on the home page. Run docker restart cbioportal-container
.
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 /<path_to_config_file>/portal.properties:/cbioportal/portal.properties:ro \
-v "$PWD/portalinfo:/portalinfo" \
-w /cbioportal/core/src/main/scripts \
cbioportal-image \
./dumpPortalInfo.pl /portalinfo
Then, grant the validation/loading command access to this folder and tell the script it to use it instead of the API:
docker run -it --rm --net cbio-net \
-v /<path_to_config_file>/portal.properties:/cbioportal/portal.properties:ro \
-v "$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
Similar to the method above, but here you open a bash shell in an otherwise idle container and run the commands there.
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 /<path_to_config_file>/portal.properties:/cbioportal/portal.properties:ro \
-v "$PWD"/study-dir:/study:ro \
-v "$HOME"/Desktop:/outdir \
cbioportal-image tail -f /dev/null
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
See the developer manual to build images based on a local copy of the source code.
When running the webserver, this command opens up port 8000 for remote debugging software to attach.
docker run --rm \
--name=cbioportal-dev \
--net=cbio-net \
-v /<path_to_config_file>/portal.properties:/cbioportal/portal.properties:ro \
-e JPDA_ADDRESS=0.0.0.0:8000
-p 127.0.0.1:8000:8000 \
-p 8080:8080 \
cbioportal-image \
catalina.sh jpda run
Debugging the Java components of the data loading pipeline presently requires applying the included patch to the code as follows. It will re-open the port before starting each step of the loading process.
docker run -it --rm \
--net cbio-net \
-p 127.0.0.1:8000:8000 \
-v "/<path_to_cbioportal-docker>/debug-loader-java.gitpatch:/mnt/debug-loader-java.gitpatch:ro" \
-v /<path_to_config_file>/portal.properties:/cbioportal/portal.properties:ro \
-v "$PWD/study-dir:/study:ro" \
cbioportal-image \
sh -c 'git apply /mnt/debug-loader-java.gitpatch && cbioportalImporter.py -s /study'
If you want to run and test code from a branch you have not checked out
locally, say from someone else’s pull request, you can use a command like the
following. This example checks out the rc
branch of the GitHub repository for
thehyve
.
docker run --rm \
-p 8081:8080 \
--net=cbio-net \
--name=cbioportal-test \
-v /<path_to_config_file>/portal.properties:/cbioportal/portal.properties:ro \
cbioportal-image \
sh -c 'git fetch https://github.com/thehyve/cbioportal.git rc && git checkout FETCH_HEAD && mvn -DskipTests clean install && rm -f "$CATALINA_HOME/webapps/cbioportal.war" && unzip portal/target/cbioportal*.war -d "$CATALINA_HOME/webapps/cbioportal/" && exec catalina.sh run'
When creating the database container, you can map a port on the
local host to port 3306 of the container running the MySQL database,
by adding an option such as -p 127.0.0.1:8306:3306
to the docker run
command before the name of the image (mysql:5.7
). You can then
connect to this port (port 8306 in this example) using MySQL
Workbench or another
MySQL client.
If you have not opened a port, the following command can still
connect a command-line client to the container (cbioDB
here)
using the --net
option:
docker run -it --rm \
--net=cbio-net \
-e MYSQL_HOST=cbioDB \
-e MYSQL_USER=cbio \
-e MYSQL_PASSWORD=P@ssword1 \
-e MYSQL_DATABASE=cbioportal \
mysql:5.7 \
sh -c 'mysql -h"$MYSQL_HOST" -u"$MYSQL_USER" -p"$MYSQL_PASSWORD" "$MYSQL_DATABASE"'