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 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
:warning: after importing a study, remember to restart cbioportal-container
to see the study on 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 /<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
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 /<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
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
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"'