diff --git a/404.html b/404.html index 6ab3df4fae2..cbe9492ea44 100644 --- a/404.html +++ b/404.html @@ -3,7 +3,7 @@ - + @@ -28,11 +28,11 @@ - + - + - + diff --git a/about-us/index.html b/about-us/index.html index e6988979f5c..adda7758165 100644 --- a/about-us/index.html +++ b/about-us/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/architecture-overview/index.html b/architecture-overview/index.html index 09e36a491d5..b127682bfe1 100644 --- a/architecture-overview/index.html +++ b/architecture-overview/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/backend-code-organization/index.html b/backend-code-organization/index.html index f0b46e38504..f5aca48d22f 100644 --- a/backend-code-organization/index.html +++ b/backend-code-organization/index.html @@ -3,7 +3,7 @@ - + @@ -33,11 +33,11 @@ - + - + - + diff --git a/backend-development-guidelines/index.html b/backend-development-guidelines/index.html index 28924e0d400..917a0859f12 100644 --- a/backend-development-guidelines/index.html +++ b/backend-development-guidelines/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/data-loading-for-developers/index.html b/data-loading-for-developers/index.html index e72a17e0bf7..ac8abb0ccd3 100644 --- a/data-loading-for-developers/index.html +++ b/data-loading-for-developers/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/data-loading-maintaining-studies/index.html b/data-loading-maintaining-studies/index.html index a4eedf6508e..88b1d4db278 100644 --- a/data-loading-maintaining-studies/index.html +++ b/data-loading-maintaining-studies/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/data-loading-tips-and-best-practices/index.html b/data-loading-tips-and-best-practices/index.html index 62d310af24c..75d04f435e2 100644 --- a/data-loading-tips-and-best-practices/index.html +++ b/data-loading-tips-and-best-practices/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/data-loading/index.html b/data-loading/index.html index 38c75005a5b..eec65729d86 100644 --- a/data-loading/index.html +++ b/data-loading/index.html @@ -3,7 +3,7 @@ - + @@ -31,12 +31,12 @@ - + - + - - + + diff --git a/deployment/authorization-and-authentication/authenticating-and-authorizing-users-via-keycloak/index.html b/deployment/authorization-and-authentication/authenticating-and-authorizing-users-via-keycloak/index.html index b05f12d58cb..7aab545677d 100644 --- a/deployment/authorization-and-authentication/authenticating-and-authorizing-users-via-keycloak/index.html +++ b/deployment/authorization-and-authentication/authenticating-and-authorizing-users-via-keycloak/index.html @@ -3,7 +3,7 @@ - + @@ -33,12 +33,12 @@ - + - + - - + + @@ -354,16 +354,39 @@

Export configuration for cBioPortal

+

There are two known ways to download the keycloak configuration (aka IDP SSO Descriptor) file for cBioPortal.

+ +

+ # + I. Download via link +

+ +

The file can be fetched by the following url:

+
+
http(s)://{KEYCLOAK-URL}/auth/realms/{REALM-NAME}/protocol/saml/descriptor
+
+

For example:

+
+
curl -o client-tailored-saml-idp-metadata.xml "http://localhost:8081/auth/realms/cbioportal/protocol/saml/descriptor"
+
+

Note: if you use https protocol with self-signed protocol you need to add --insecure option to the above curl command.

+ +

+ # + II. Export via GUI (legacy) +

+
  1. Next, navigate to the Installation tab for the same client.
    2. -
  2. Select SAML Metadata IDPSSODescriptor as the Format Option and click the Download button.
    3. -
  3. Move the downloaded XML file to portal/src/main/resources/ if you're compiling cBioPortal yourself or if you're using the Docker container, mount the file in the /cbioportal-webapp folder with -v /path/to/client-tailored-saml-idp-metadata.xml:/cbioportal-webapp/WEB-INF/classes/client-tailored-saml-idp-metadata.xml. +
  4. Select SAML Metadata IDPSSODescriptor as the Format Option and click the Download button. +⚠️ This GUI option has been removed from the newer versions of Keycloak.
+

After you've downloaded the XML file with one of the above ways, move it to portal/src/main/resources/ if you're compiling cBioPortal yourself or if you're using the Docker container, mount the file in the /cbioportal-webapp folder with -v /path/to/client-tailored-saml-idp-metadata.xml:/cbioportal-webapp/WEB-INF/classes/client-tailored-saml-idp-metadata.xml.

# @@ -523,6 +546,7 @@

+

Note: if filter_groups_by_appname is set to false as specified above, the Role Name has to match with an id of the study you would give access to by assigning this role. Otherwise, if filter_groups_by_appname is set to true (DEFAULT), you have to add the application name (app.name) followed by the colon as a prefix to the study id. e.g. cbioportal:brca_tcga_pub

# @@ -878,24 +902,9 @@

Getting this to work requires many steps, and can be a bit tricky. If you get stuck or get an obscure error message, your best bet is to turn on all DEBUG logging. -This can be done via src/main/resources/logback.xml. For example:

-
-
<root level="debug">
-    <appender-ref ref="STDOUT" />
-    <appender-ref ref="FILE" />
-</root>
-
-<logger name="org.mskcc" level="debug">
-    <appender-ref ref="STDOUT" />
-    <appender-ref ref="FILE" />
-</logger>
-
-<logger name="org.cbioportal.security" level="debug">
-    <appender-ref ref="STDOUT" />
-    <appender-ref ref="FILE" />
-</logger>
-
+This can be done via src/main/resources/logback.xml. See logback.DEBUG.EXAMPLE.xml file for an example of how to configure debug levels for cbioportal.

Then, rebuild the WAR, redeploy, and try to authenticate again. Your log file will then include hundreds of SAML-specific messages, even the full XML of each SAML message, and this should help you debug the error.

+

If you're using the Docker container, mount the file instead with -v ./logback.xml:/cbioportal-webapp/WEB-INF/classes/logback.xml.

# diff --git a/deployment/authorization-and-authentication/authenticating-users-via-ldap/index.html b/deployment/authorization-and-authentication/authenticating-users-via-ldap/index.html index 73c8cac3b6b..75aed6554a6 100644 --- a/deployment/authorization-and-authentication/authenticating-users-via-ldap/index.html +++ b/deployment/authorization-and-authentication/authenticating-users-via-ldap/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/deployment/authorization-and-authentication/authenticating-users-via-saml/index.html b/deployment/authorization-and-authentication/authenticating-users-via-saml/index.html index 06fed87f581..f53647d676c 100644 --- a/deployment/authorization-and-authentication/authenticating-users-via-saml/index.html +++ b/deployment/authorization-and-authentication/authenticating-users-via-saml/index.html @@ -3,7 +3,7 @@ - + @@ -33,11 +33,11 @@ - + - + - + diff --git a/deployment/authorization-and-authentication/authenticating-users-via-tokens/index.html b/deployment/authorization-and-authentication/authenticating-users-via-tokens/index.html index 558481ee06a..97bbb52afb5 100644 --- a/deployment/authorization-and-authentication/authenticating-users-via-tokens/index.html +++ b/deployment/authorization-and-authentication/authenticating-users-via-tokens/index.html @@ -3,7 +3,7 @@ - + @@ -33,11 +33,11 @@ - + - + - + diff --git a/deployment/authorization-and-authentication/logback.debug.example.xml b/deployment/authorization-and-authentication/logback.debug.example.xml new file mode 100644 index 00000000000..c4faf8c5412 --- /dev/null +++ b/deployment/authorization-and-authentication/logback.debug.example.xml @@ -0,0 +1,29 @@ + + + + %d{HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n + + + + + /tmp/cbioportal.log + + %date %level [%thread] %logger{10} [%file:%line] %msg%n + + + + + + + + + + + + + + + + + + diff --git a/deployment/authorization-and-authentication/user-authorization/index.html b/deployment/authorization-and-authentication/user-authorization/index.html index f59698191cf..612a290e4e8 100644 --- a/deployment/authorization-and-authentication/user-authorization/index.html +++ b/deployment/authorization-and-authentication/user-authorization/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/deployment/customization/caching/index.html b/deployment/customization/caching/index.html index 89902ef7e98..9800603ecd1 100644 --- a/deployment/customization/caching/index.html +++ b/deployment/customization/caching/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/deployment/customization/customizing-your-instance-of-cbioportal/index.html b/deployment/customization/customizing-your-instance-of-cbioportal/index.html index 0569326af8b..74e5bcaee58 100644 --- a/deployment/customization/customizing-your-instance-of-cbioportal/index.html +++ b/deployment/customization/customizing-your-instance-of-cbioportal/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/deployment/customization/portal.properties-reference/index.html b/deployment/customization/portal.properties-reference/index.html index c8b52d29e57..9e4711269c8 100644 --- a/deployment/customization/portal.properties-reference/index.html +++ b/deployment/customization/portal.properties-reference/index.html @@ -3,7 +3,7 @@ - + @@ -33,12 +33,12 @@ - + - + - - + + diff --git a/deployment/customization/studyview/index.html b/deployment/customization/studyview/index.html index a39db4b47a9..73a348abecb 100644 --- a/deployment/customization/studyview/index.html +++ b/deployment/customization/studyview/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/deployment/deploy-without-docker/build-from-source/index.html b/deployment/deploy-without-docker/build-from-source/index.html index 6350521cb0c..2a0e413cd69 100644 --- a/deployment/deploy-without-docker/build-from-source/index.html +++ b/deployment/deploy-without-docker/build-from-source/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/deployment/deploy-without-docker/deploying/index.html b/deployment/deploy-without-docker/deploying/index.html index 32fce0c5f38..977c9ce2287 100644 --- a/deployment/deploy-without-docker/deploying/index.html +++ b/deployment/deploy-without-docker/deploying/index.html @@ -3,7 +3,7 @@ - + @@ -31,12 +31,12 @@ - + - + - - + + diff --git a/deployment/deploy-without-docker/import-the-seed-database/index.html b/deployment/deploy-without-docker/import-the-seed-database/index.html index 6e994e9f383..73fb4420ed2 100644 --- a/deployment/deploy-without-docker/import-the-seed-database/index.html +++ b/deployment/deploy-without-docker/import-the-seed-database/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/deployment/deploy-without-docker/load-sample-cancer-study/index.html b/deployment/deploy-without-docker/load-sample-cancer-study/index.html index 0ede9891ea6..1ba63402382 100644 --- a/deployment/deploy-without-docker/load-sample-cancer-study/index.html +++ b/deployment/deploy-without-docker/load-sample-cancer-study/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/deployment/deploy-without-docker/pre-build-steps/index.html b/deployment/deploy-without-docker/pre-build-steps/index.html index 42c4a5b44c3..e43f513e408 100644 --- a/deployment/deploy-without-docker/pre-build-steps/index.html +++ b/deployment/deploy-without-docker/pre-build-steps/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/deployment/deploy-without-docker/software-requirements/index.html b/deployment/deploy-without-docker/software-requirements/index.html index 10064f1f99c..129e6c1e8ab 100644 --- a/deployment/deploy-without-docker/software-requirements/index.html +++ b/deployment/deploy-without-docker/software-requirements/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/deployment/docker/example_commands/index.html b/deployment/docker/example_commands/index.html index 1bef186e756..3086c97e638 100644 --- a/deployment/docker/example_commands/index.html +++ b/deployment/docker/example_commands/index.html @@ -3,7 +3,7 @@ - + @@ -31,12 +31,12 @@ - + - + - - + + diff --git a/deployment/docker/import_data/index.html b/deployment/docker/import_data/index.html index 30b7f55a778..43e94dabf8b 100644 --- a/deployment/docker/import_data/index.html +++ b/deployment/docker/import_data/index.html @@ -3,7 +3,7 @@ - + @@ -31,12 +31,12 @@ - + - + - - + + diff --git a/deployment/docker/index.html b/deployment/docker/index.html index d16e503dba9..b330bb514b5 100644 --- a/deployment/docker/index.html +++ b/deployment/docker/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/deployment/docker/notes-for-non-linux/index.html b/deployment/docker/notes-for-non-linux/index.html index 5e428116c65..dd105398fd9 100644 --- a/deployment/docker/notes-for-non-linux/index.html +++ b/deployment/docker/notes-for-non-linux/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/deployment/docker/using-keycloak/index.html b/deployment/docker/using-keycloak/index.html index 471a69cc823..34616693118 100644 --- a/deployment/docker/using-keycloak/index.html +++ b/deployment/docker/using-keycloak/index.html @@ -3,7 +3,7 @@ - + @@ -31,12 +31,12 @@ - + - + - - + + diff --git a/deployment/index.html b/deployment/index.html index 0759f2422c9..fb9df8928bd 100644 --- a/deployment/index.html +++ b/deployment/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/deployment/integration-with-other-webservices/index.html b/deployment/integration-with-other-webservices/index.html index a9fb77b380b..79ed9b1b000 100644 --- a/deployment/integration-with-other-webservices/index.html +++ b/deployment/integration-with-other-webservices/index.html @@ -3,7 +3,7 @@ - + @@ -28,11 +28,11 @@ - + - + - + diff --git a/deployment/integration-with-other-webservices/oncokb-data-access/index.html b/deployment/integration-with-other-webservices/oncokb-data-access/index.html index e6b18dd5ca0..4c5f2347d1c 100644 --- a/deployment/integration-with-other-webservices/oncokb-data-access/index.html +++ b/deployment/integration-with-other-webservices/oncokb-data-access/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/development/build-different-frontend/index.html b/development/build-different-frontend/index.html index 2d5758b2043..ff10389ce99 100644 --- a/development/build-different-frontend/index.html +++ b/development/build-different-frontend/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/development/cbioportal-er-diagram/index.html b/development/cbioportal-er-diagram/index.html index eab82042077..449077e69f1 100644 --- a/development/cbioportal-er-diagram/index.html +++ b/development/cbioportal-er-diagram/index.html @@ -3,7 +3,7 @@ - + @@ -33,11 +33,11 @@ - + - + - + diff --git a/development/database-versioning/index.html b/development/database-versioning/index.html index 1eef9464eb1..8c019e496b2 100644 --- a/development/database-versioning/index.html +++ b/development/database-versioning/index.html @@ -3,7 +3,7 @@ - + @@ -31,12 +31,12 @@ - + - + - - + + diff --git a/development/deployment-procedure/index.html b/development/deployment-procedure/index.html index 86604872c63..4dd3346fce6 100644 --- a/development/deployment-procedure/index.html +++ b/development/deployment-procedure/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/development/documentation-site/index.html b/development/documentation-site/index.html index a1d4c3651d7..54d589ec992 100644 --- a/development/documentation-site/index.html +++ b/development/documentation-site/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/development/feature-development-guide/index.html b/development/feature-development-guide/index.html index 88a475aad6c..eb4788f8f16 100644 --- a/development/feature-development-guide/index.html +++ b/development/feature-development-guide/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/development/index.html b/development/index.html index 50b43ccc31c..db0036739cd 100644 --- a/development/index.html +++ b/development/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/development/manual-test-cases/index.html b/development/manual-test-cases/index.html index 5f0702bff7e..4891cde9f98 100644 --- a/development/manual-test-cases/index.html +++ b/development/manual-test-cases/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/development/release-procedure/index.html b/development/release-procedure/index.html index 8d3b0700d5c..f11f6c6c22a 100644 --- a/development/release-procedure/index.html +++ b/development/release-procedure/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/development/session-service-working/index.html b/development/session-service-working/index.html index 80075b44538..8c4809c60d0 100644 --- a/development/session-service-working/index.html +++ b/development/session-service-working/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/downloads/index.html b/downloads/index.html index dc9a55d7e34..473ef8ca72a 100644 --- a/downloads/index.html +++ b/downloads/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/file-formats/index.html b/file-formats/index.html index 1f0c4b18989..edb82bc6a82 100644 --- a/file-formats/index.html +++ b/file-formats/index.html @@ -3,7 +3,7 @@ - + @@ -33,12 +33,12 @@ - + - + - - + + diff --git a/hardware-requirements/index.html b/hardware-requirements/index.html index 8f756205b0d..2701230131a 100644 --- a/hardware-requirements/index.html +++ b/hardware-requirements/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/import-gene-panels/index.html b/import-gene-panels/index.html index be277904b20..7bab6e89a4b 100644 --- a/import-gene-panels/index.html +++ b/import-gene-panels/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/import-gene-sets/index.html b/import-gene-sets/index.html index af3d00b04ac..d78a0931f68 100644 --- a/import-gene-sets/index.html +++ b/import-gene-sets/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/import-oncokb-annotations-as-custom-driver-annotations/index.html b/import-oncokb-annotations-as-custom-driver-annotations/index.html index 8ebe0688dac..3829b4278e7 100644 --- a/import-oncokb-annotations-as-custom-driver-annotations/index.html +++ b/import-oncokb-annotations-as-custom-driver-annotations/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/import-reference-genome/index.html b/import-reference-genome/index.html index 08e6d971c92..0df30bf4174 100644 --- a/import-reference-genome/index.html +++ b/import-reference-genome/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/import-study-using-docker/index.html b/import-study-using-docker/index.html index e47aba0f5c1..fb5d217fa4f 100644 --- a/import-study-using-docker/index.html +++ b/import-study-using-docker/index.html @@ -3,7 +3,7 @@ - + @@ -31,12 +31,12 @@ - + - + - - + + diff --git a/imported-maf-columns/index.html b/imported-maf-columns/index.html index 2ff5296a7ef..129942f546c 100644 --- a/imported-maf-columns/index.html +++ b/imported-maf-columns/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/importer-tool/index.html b/importer-tool/index.html index 27ad89b24fb..cb497e31af7 100644 --- a/importer-tool/index.html +++ b/importer-tool/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/index.html b/index.html index 2efbf4d5e64..70fa2a9a6ce 100644 --- a/index.html +++ b/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/migration-guide/index.html b/migration-guide/index.html index 623be559d38..7261d7f0f6e 100644 --- a/migration-guide/index.html +++ b/migration-guide/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/msk-maintenance/index.html b/msk-maintenance/index.html index 154ee56f82f..d389636f380 100644 --- a/msk-maintenance/index.html +++ b/msk-maintenance/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/mutation-data-transcript-annotation/index.html b/mutation-data-transcript-annotation/index.html index 2578d1b1c25..0649d849843 100644 --- a/mutation-data-transcript-annotation/index.html +++ b/mutation-data-transcript-annotation/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/news-genie/index.html b/news-genie/index.html index 21a35a69d2b..0f33fafaa73 100644 --- a/news-genie/index.html +++ b/news-genie/index.html @@ -3,7 +3,7 @@ - + @@ -31,11 +31,11 @@ - + - + - + diff --git a/news/index.html b/news/index.html index e97b85546e3..44653711b52 100644 --- a/news/index.html +++ b/news/index.html @@ -3,7 +3,7 @@ - + @@ -33,11 +33,11 @@ - + - + - + diff --git a/resources/js/config.js b/resources/js/config.js index ac0072701b6..81c81be3ca6 100644 --- a/resources/js/config.js +++ b/resources/js/config.js @@ -1 +1 @@ -var __DOCS_CONFIG__ = 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Group","We maintain an active list of RFCs (Requests for Comments) where we describe new features and solicit community feedback.","FAQ","Tutorials","API documentation"]}],[{"l":"About Us","p":["The cBioPortal for Cancer Genomics was originally developed at Memorial Sloan Kettering Cancer Center(MSK). The public cBioPortal site is hosted by the Center for Molecular Oncology at MSK. The cBioPortal software is now available under an open source license via GitHub. The software is now developed and maintained by a multi-institutional team, consisting of MSK, the Dana Farber Cancer Institute, Princess Margaret Cancer Centre in Toronto, Children's Hospital of Philadelphia, Caris Life Sciences, The Hyve and SE4BIO in the Netherlands, and Bilkent University in Ankara, Turkey."]},{"l":"Memorial Sloan Kettering Cancer Center","p":["Aaron Lisman","Angelica Ochoa","Anusha Satravada","Avery Wang","Benjamin Gross","Bryan Lai","Calla Chennault","Gaofei Zhao","Hongxin Zhang","Ino de Bruijn","Manda Wilson","Nikolaus Schultz","Ramyasree Madupuri","Rima AlHamad","Ritika Kundra","Robert Sheridan","S Onur Sumer","Xiang Li"]},{"l":"Dana-Farber Cancer Institute","p":["Ethan Cerami","Tali Mazor","Jeremy Easton-Marks","Zhaoyuan (Ryan) Fu","Augustin Luna","James Lindsay","Chris Sander"]},{"i":"princess-margaret-cancer-centre-toronto","l":"Princess Margaret Cancer Centre, Toronto","p":["Prasanna Jagannathan","Trevor Pugh"]},{"i":"childrens-hospital-of-philadelphia","l":"Children's Hospital of Philadelphia","p":["Charles Haynes","David Higgins","Allison Heath","John Maris","Adam Resnick","Miguel Brown"]},{"l":"Caris Life Sciences","p":["Jianjiong Gao","Priti Kumari","Karthik Kalletla"]},{"l":"The Hyve","p":["Oleguer Plantalech","Pim van Nierop","Sander Rodenburg","Bas Leenknegt","Elena G Lara","Jessica Singh","Matthijs Pon","Tim Kuijpers","Mirella Kalafati","Sjoerd van Hagen"]},{"l":"SE4BIO","p":["Pieter Lukasse","Ruslan Forostianov"]},{"l":"Bilkent University","p":["Ugur Dogrusoz","Yusuf Ziya Ozgul"]},{"l":"Alumni","p":["Adam Abeshouse","Alexandros Sigaras","Anders Jacobsen","Andy Dufilie","Arthur Goldberg","B Arman Aksoy","Caitlin Byrne","Catherine Del Vecchio Fitz","Diana Baiceanu","Dionne Zaal","Divya Madala","Dong Li","Erik Larsson","Ersin Ciftci","Fedde Schaeffer","Fred Criscuolo","Gideon Dresdner","Hsiao-Wei Chen","Irina Pulyakhina","Istemi Bahceci","James Xu","Jiaojiao Wang","Jing Su","Kaan Sancak","Kees van Bochove","Kelsey Zhu","Leonard Dervishi","Luke Sikina","M Furkan Sahin","M Salih Altun","Michael Heuer","Ngoc Nguyen","Olivier Elemento","Paul van Dijk","Peter Kok","Pichai Raman","Riza Nugraha","Sander Tan","Stuart Watt","Tamba Monrose","Yichao Sun","Zachary Heins","Ziya Erkoc"]},{"i":"funding-for-the-cbioportal-for-cancer-genomics-is-or-has-been-provided-by","l":"Funding for the cBioPortal for Cancer Genomics is or has been provided by:"},{"i":"current","l":"Current:","p":["NCI, through ITCR grant NCI-U24CA274633 and HTAN grant NCI-U24CA233243","Marie-José and Henry R. Kravis Center for Molecular Oncology at MSK","Dana Farber Cancer Institute","American Association for Cancer Research through AACR Project GENIE","Prostate Cancer Foundation","The Cholangiocarcinoma Foundation","Robertson Foundation"]},{"i":"past","l":"Past:","p":["NCI, through ITCR grant NCI-U24CA220457","Stand Up 2 Cancer","The Ben & Catherine Ivy Foundation","NCI, as a TCGA Genome Data Analysis Center (GDAC)(NCI-U24CA143840)","NCRR, as the National Resource for Network Biology (NRNB) Research Resource (RR 031228-02)","Starr Cancer Consortium","Breast Cancer Research Foundation","Adenoid Cystic Carcinoma Research Foundation","POETIC Consortium","Parker Institute for Cancer Immunotherapy"]}],[{"l":"List of Active RFCs","p":["We maintain an active set of RFCs (Requests for Comments) where we spec out new features and solicit community feedback.","See this shared google folder for the list of RFCs."]},{"l":"For Developers Creating new RFCs","p":["Use the RFC Template","Create your RFC within this shared google folder, and pick a new incremental number.","Add a Link to your RFC on this page."]}],[{"l":"User Guide","p":["The cBioPortal for Cancer Genomics is a resource for interactive exploration of multidimensional cancer genomics data sets. The goal of cBioPortal is to significantly lower the barriers between complex genomic data and cancer researchers by providing rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects, and therefore to empower researchers to translate these rich data sets into biologic insights and clinical applications.","The following section guides users in performing queries and analysis on any instance of cBioportal."]}],[{"l":"New Users","p":["Are you new to cBioPortal? Welcome! We have a few options to help you get started.","If you have an hour, we highly recommend watching the recording of our Introduction to cBioPortal webinar ( youtube.com or bilibili.com).","Don't have an hour? Review our tutorial slides for exploring a study ( Google slides or PDF) and running a query ( Google slides or PDF)","Or, watch two of our short how-to videos which demonstrate how to explore a study ( youtube.com) and how to run a query ( youtube.com)."]}],[{"l":"cBioPortal FAQs","p":["Analysis Questions","Are there any normal tissue samples available through cBioPortal?","Can I change the order of genes in the OncoPrint?","Can I create a local instance of cBioPortal to host my own data?","Can I download all data at once?","Can I save or bookmark my results in cBioPortal?","Can I use cBioPortal with my own data?","Can I use figures from the cBioPortal in my publications or presentations?","Can I visualize my own data within an OncoPrint?","Clinical Data","Data Questions","DNA (Mutations, Copy Number & Fusions)","DNA Methylation","Does the cBioPortal contain synonymous mutation data?","Does the cBioPortal provide a Web Service API? R interface? MATLAB interface?","Does the Mutual Exclusivity tab calculate its statistics using all samples/alterations or only a specific subset?","Does the portal contain cancer study X?","Does the portal store raw or probe-level data?","Does the portal work on all browsers and operating systems?","General Data","General Questions","How are protein domains in the mutational lollipop diagrams specified?","How can I compare outcomes in patients with high vs low expression of a gene?","How can I compare two or more subsets of samples?","How can I create a subset or sub cohort of a study with specific samples or patients?","How can I download the PanCancer Atlas data?","How can I find which studies have mRNA expression data (or any other specific data type)?","How can I form a combined Study?","How can I query microRNAs in the portal?","How can I query over/under expression of a gene?","How can I query phosphoprotein levels in the portal?","How can I query/explore a select subset of samples?","How do I access data from AACR Project GENIE?","How do I cite the cBioPortal?","How do I get started?","How do I get updates on new portal developments and new data sets?","How does cBioPortal handle duplicate samples or sample IDs across different studies?","How does TCGA data in cBioPortal compare to TCGA data in Genome Data Commons?","How is TCGA RNASeqV2 processed? What units are used?","How is the cBioPortal for Cancer Genomics different from the Genomic Data Commons (GDC)?","How to use filter in the URL of Study View page?","I'd like to contribute code to the cBioPortal. How do I get started?","Is it necessary to log in to use virtual studies? If I do log in, what additional functionality do I gain?","Is it possible to determine if a particular mutation is heterozygous or homozygous in a sample? When a sample has 2 mutations in one gene, is it possible to determine whether the mutations are in cis or in trans with each other?","Is there any normal RNA-seq data in cBioPortal?","Is there microRNA data?","OncoPrint","Other pages","Protein","Results View","RNA","Study View","TCGA","The data today is different than the last time i looked. What happened?","What are mRNA and microRNA Z-Scores?","What are OncoPrints?","What are TCGA Firehose Legacy datasets and how do they compare to the publication-associated datasets and the PanCancer Atlas datasets?","What are the statistical significance tests in Group Comparison?","What are the values of the box and whiskers in a boxplot?","What data types are in the portal?","What do “Amplification”, “Gain”, “Deep Deletion”, “Shallow Deletion” and \"-2\", \"-1\", \"0\", \"1\", and \"2\" mean in the copy-number data?","What does ___ stand for?","What happened to TCGA Provisional datasets?","What if I have other questions or comments?","What is a combined Study?","What is a Virtual Study?","What is GISTIC? What is RAE?","What is Group Comparison?","What is the cBioPortal for Cancer Genomics?","What is the difference between a “splice site” mutation and a “splice region” mutation?","What is the meaning of OS_STATUS / OS_MONTHS, and PFS_STATUS / PFS_MONTHS?","What is the process of data curation?","What kind of clinical data is stored in the portal?","What processing or filtering is applied to generate the mutation data?","What transcripts are used for annotating mutations?","What version of the human reference genome is being used in cBioPortal?","Where do the thresholded copy number call in TCGA Firehose Legacy data come from?","Which methylation probe is used for genes with multiple probes?","Which resources are integrated for variant annotation?","Which studies have MutSig and GISTIC results? How do these results compare to the data in the TCGA publications?","Why are some samples “Not profiled” for certain genes?","Why isn’t there protein data for my gene of interest?"]},{"l":"General Questions"},{"i":"what-is-the-cbioportal-for-cancer-genomics","l":"What is the cBioPortal for Cancer Genomics?","p":["The cBioPortal for Cancer Genomics is an open-access, open-source resource for interactive exploration of multidimensional cancer genomics data sets. The goal of cBioPortal is to significantly lower the barriers between complex genomic data and cancer researchers by providing rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects, and therefore to empower researchers to translate these rich data sets into biologic insights and clinical applications."]},{"i":"how-do-i-get-started","l":"How do I get started?","p":["Check out our tutorial slides to get started or go through our tutorial paper."]},{"i":"what-data-types-are-in-the-portal","l":"What data types are in the portal?","p":["The portal supports and stores non-synonymous mutations, DNA copy-number data (putative, discrete values per gene, e.g. \"deeply deleted\" or \"amplified\", as well as log2 or linear copy number data), mRNA and microRNA expression data, protein-level and phosphoprotein level data (RPPA or mass spectrometry based), DNA methylation data, and de-identified clinical data. For a complete breakdown of available data types per cancer study go to the Data Sets Page. Note that for many studies, only somatic mutation data and limited clinical data are available. For TCGA studies, the other data types are also available. Germline mutations are supported by cBioPortal, but are, with a few exceptions, not available in the public instance."]},{"i":"what-does-___-stand-for","l":"What does ___ stand for?","p":["Here are the meanings of some of the abbreviations used by cBioPortal:","VUS: variant of unknown significance","CNA: copy number alteration","AMP: amplification","HOMDEL: deep deletion","TMB: tumor mutational burden, calculated as mutations per megabase of sequenced DNA","KM: Kaplan-Meier","MSI: microsatellite instability","OQL: Onco Query Language, used within cBioPortal to define the types of alterations included in a query. For more on OQL, review the documentation, tutorial slides, and videos"]},{"i":"what-is-the-process-of-data-curation","l":"What is the process of data curation?","p":["The TCGA firehose legacy datasets are imported directly from the original TCGA Data Coordinating Center via the Broad Firehose.","We are also actively curating datasets from the literature. Studies from the literature were curated from the data published with the manuscripts. We sometimes reach out to the investigators to acquire additional data, such as clinical attributes. All mutation calls (in VCF or MAF format) are processed through an internal pipeline to annotate the variant effects in a consistent way across studies. Please contact us to suggest additional public datasets to curate or view the list of studies suggested for curation in our Datahub on Github."]},{"i":"how-do-i-get-updates-on-new-portal-developments-and-new-data-sets","l":"How do I get updates on new portal developments and new data sets?","p":["Please subscribe to our low-volume news mailing list or follow @cbioportal on Twitter."]},{"i":"does-the-portal-work-on-all-browsers-and-operating-systems","l":"Does the portal work on all browsers and operating systems?","p":["We support and test on the following web browsers: Safari, Google Chrome, Firefox and Edge. (As of release v3.5.4 we no longer support Internet Explorer 11). If you notice any incompatibilities, please let us know."]},{"i":"how-do-i-cite-the-cbioportal","l":"How do I cite the cBioPortal?","p":["Please cite the following portal papers:","Cerami et al. The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics Data. Cancer Discovery. May 2012 2; 401. PubMed.","Gao et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci. Signal. 6, pl1 (2013). PubMed.","de Bruijn et al. Analysis and Visualization of Longitudinal Genomic and Clinical Data from the AACR Project GENIE Biopharma Collaborative in cBioPortal. Cancer Res (2023). PubMed.","Remember also to cite the source of the data if you are using a publicly available dataset."]},{"i":"can-i-use-figures-from-the-cbioportal-in-my-publications-or-presentations","l":"Can I use figures from the cBioPortal in my publications or presentations?","p":["Yes, you are free to use any of the figures from the portal in your publications or presentations (many are available in SVG or PDF format for easier scaling and editing). When you do, please cite Cerami et al., Cancer Discov. 2012, and Gao et al., Sci. Signal. 2013 (see the previous question for full citations)."]},{"i":"can-i-save-or-bookmark-my-results-in-cbioportal","l":"Can I save or bookmark my results in cBioPortal?","p":["You can bookmark your query results and share the URL with collaborators. We store all queries via Session IDs, and these are saved indefinitely. Use the bookmark tab to retrieve the full link, or generate a short link via the bit.ly link generator."]},{"i":"how-is-the-cbioportal-for-cancer-genomics-different-from-the-genomic-data-commons-gdc","l":"How is the cBioPortal for Cancer Genomics different from the Genomic Data Commons (GDC)?","p":["The cBioPortal is an exploratory analysis tool for exploring large-scale cancer genomic data sets that hosts data from large consortium efforts, like TCGA and TARGET, as well as publications from individual labs. You can quickly view genomic alterations across a set of patients, across a set of cancer types, perform survival analysis and perform group comparisons. If you want to explore specific genes or a pathway of interest in one or more cancer types, the cBioPortal is probably where you want to start.","By contrast, the Genomic Data Commons (GDC) aims to be the definitive place for full-download and access to all data generated by TCGA and TARGET. If you want to download raw mRNA expression files or full segmented copy number files, the GDC is probably where you want to start."]},{"i":"does-the-cbioportal-provide-a-web-service-api-r-interface-matlab-interface","l":"Does the cBioPortal provide a Web Service API? R interface? MATLAB interface?","p":["Yes, the cBioPortal provides a Swagger API, and R/MATLAB interfaces."]},{"i":"can-i-use-cbioportal-with-my-own-data","l":"Can I use cBioPortal with my own data?","p":["cBioPortal provides several options for analyzing your own data. Visit our Visualize Your Data page to generate an OncoPrint or Lollipop Plot with your own data. To utilize the entire suite of analysis and visualization tools, you can also install your own instance of cBioPortal (see next question)."]},{"i":"can-i-create-a-local-instance-of-cbioportal-to-host-my-own-data","l":"Can I create a local instance of cBioPortal to host my own data?","p":["Yes, the cBioPortal is open-source, and available on GitHub. Our documentation provides complete download and installation instructions."]},{"i":"id-like-to-contribute-code-to-the-cbioportal-how-do-i-get-started","l":"I'd like to contribute code to the cBioPortal. How do I get started?","p":["Great! We would love to have your contributions. To get started, head over to our GitHub repository and check out our page on how to contribute."]},{"i":"what-is-a-combined-study","l":"What is a combined Study?","p":["A combined study is a custom study comprised of samples from multiple studies. The combined study feature enables you to combine samples from multiple studies to form a bigger study. This cohort of samples can then be queried or explored just like a traditional study, and can be returned to at a later date or shared with a collaborator."]},{"i":"how-can-i-form-a-combined-study","l":"How can I form a combined Study?","p":["A combined or merged study is a custom study comprised of samples from multiple studies. In the homepage of cbioportal, studies can be selected using the checkbox located on the left of the study. Once the studies are selected, they can be combined and explored using the \"Explore Selected Studies\" button. Alternatively, after the studies are selected, you can run queries on the combined study using the \"Query by Gene\" button."]},{"i":"how-can-i-create-a-subset-or-sub-cohort-of-a-study-with-specific-samples-or-patients","l":"How can I create a subset or sub cohort of a study with specific samples or patients?","p":["A subset or sub cohort of a study can be created by specifying individual patients or samples. After a study is selected, user can click on the \"Custom selection\" button to create a new filter by specifying the sampleID or patientID that the user is interested to explore. Another way is to filter a set of patients using the charts on the study view and then view the IDs of the patients and samples that were selected or unselected based on the current filter."]},{"i":"what-is-a-virtual-study","l":"What is a Virtual Study?","p":["A virtual study is a custom study comprised of samples from one or more existing studies. The virtual study feature allows you to define a custom cohort of samples that fit your specific genomic or clinical criteria of interest. These samples can be a subset of the data available in an existing study, or result from the combination of multiple existing studies. This cohort of samples can then be queried or explored just like a traditional study, and can be returned to at a later date or shared with a collaborator. For more information and examples, see our tutorial on virtual studies."]},{"i":"is-it-necessary-to-log-in-to-use-virtual-studies-if-i-do-log-in-what-additional-functionality-do-i-gain","l":"Is it necessary to log in to use virtual studies? If I do log in, what additional functionality do I gain?","p":["No. A user that has not logged in can create virtual studies and run queries in those studies (by using the query box on the study summary page). Links to virtual studies are permanent, so you can save the link on your computer and come back to it anytime, or share it with others.","If you log in, you gain the ability to save your virtual study to the list of existing studies on the homepage. This makes a virtual study functionally the same as any other study: you can access your virtual studies in the query builder and you can combine an existing virtual study with any other study to create a new virtual study."]},{"i":"what-is-group-comparison","l":"What is Group Comparison?","p":["Group Comparison is a suite of analysis features which allows a user to compare clinical or genomic features of user-defined groups of samples. These groups can be defined based on any clinical or genomic features. For an overview, see our tutorial on group comparison."]},{"i":"what-are-the-statistical-significance-tests-in-group-comparison","l":"What are the statistical significance tests in Group Comparison?","p":["Survival tab: Log-rank test","Clinical tab:","Continuous data: Chi-squared test","Categorical data: Kruskal Wallis test","Other tabs","2 groups","Continuous data: one-sided t-test","Categorical data: two-sided Fisher's exact test","3 or more groups","Continuous data: one-way ANOVA","Categorical data: Chi-squared test"]},{"l":"Data Questions"},{"l":"General Data"},{"i":"does-the-portal-contain-cancer-study-x","l":"Does the portal contain cancer study X?","p":["Check out the Data Sets Page for the complete set of cancer studies currently stored in the portal. If you do not see your specific cancer study of interest, please contact us, and we will let you know if it's in the queue."]},{"i":"which-resources-are-integrated-for-variant-annotation","l":"Which resources are integrated for variant annotation?","p":["cBioPortal supports the annotation of variants from several different databases. These databases provide information about the recurrence of, or prior knowledge about, specific amino acid changes. For each variant, the number of occurrences of mutations at the same amino acid position present in the COSMIC database are reported. Furthermore, variants are annotated as “hotspots” if the amino acid positions were found to be recurrent linear hotspots, as defined by the Cancer Hotspots method ( cancerhotspots.org), or three-dimensional hotspots, as defined by 3D Hotspots ( 3dhotspots.org). Prior knowledge about variants, including clinical actionability information, is provided from three different sources: OncoKB ( www.oncokb.org), CIViC ( civicdb.org), as well as My Cancer Genome ( mycancergenome.org). For OncoKB, exact levels of clinical actionability are displayed in cBioPortal, as defined by the OncoKB paper."]},{"i":"what-version-of-the-human-reference-genome-is-being-used-in-cbioportal","l":"What version of the human reference genome is being used in cBioPortal?","p":["The public cBioPortal is currently using hg19/GRCh37."]},{"i":"how-does-cbioportal-handle-duplicate-samples-or-sample-ids-across-different-studies","l":"How does cBioPortal handle duplicate samples or sample IDs across different studies?","p":["The cBioPortal generally assumes that samples or patients that have the same ID are actually the same. This is important for cross-cancer queries, where each sample should only be counted once. If a sample is part of multiple cancer cohorts, its alterations are only counted once in the Mutations tab (it will be listed multiple times in the table, but is only counted once in the lollipop plot). However, other tabs (including OncoPrint and Cancer Types Summary) will count the sample twice - for this reason, we advise against querying multiple studies that contain the same samples (e.g., TCGA PanCancer Atlas and TCGA Firehose Legacy)."]},{"i":"are-there-any-normal-tissue-samples-available-through-cbioportal","l":"Are there any normal tissue samples available through cBioPortal?","p":["No, we currently do not store any normal tissue data in our system."]},{"i":"how-can-i-find-which-studies-have-mrna-expression-data-or-any-other-specific-data-type","l":"How can I find which studies have mRNA expression data (or any other specific data type)?","p":["Check out the Data Sets Page where you can view the complete set of cancer studies and sort by the number of samples with data available for any data type."]},{"i":"can-i-download-all-data-at-once","l":"Can I download all data at once?","p":["You can download all data for individual studies on the Data Sets Page or the study view page for the study of interest. You can also download all studies from our Data Hub."]},{"i":"the-data-today-is-different-than-the-last-time-i-looked-what-happened","l":"The data today is different than the last time I looked. What happened?","p":["We do occasionally update existing datasets to provide the most up-to-date, accurate and consistent data possible. The data you see today is likely an improved version of what you have seen previously. However, if you suspect that there is an error in the current version, please let us know at cbioportal@googlegroups.com.","If you need to reference an old version of a dataset, you can find previous versions in our Datahub repository."]},{"i":"how-do-i-access-data-from-aacr-project-genie","l":"How do I access data from AACR Project GENIE?","p":["Data from AACR Project GENIE are provided in a dedicated instance of cBioPortal. You can also download GENIE data from the Synapse Platform. Note that you will need to register before accessing the data. Additional information about AACR Project GENIE can be found on the AACR website."]},{"l":"TCGA"},{"i":"how-does-tcga-data-in-cbioportal-compare-to-tcga-data-in-genome-data-commons","l":"How does TCGA data in cBioPortal compare to TCGA data in Genome Data Commons?","p":["We do not currently load the mutation data from the GDC. Instead, we have the original mutation data generated by the individual TCGA sequencing centers. The source of the data is the Broad Firehose (or the publication pages for data that matches a specific manuscript). These data are usually a combination of two mutation callers, but they differ by center (typically a variant caller like MuTect plus an indel caller), and sequencing centers have modified their mutation calling pipelines over time."]},{"i":"what-happened-to-tcga-provisional-datasets","l":"What happened to TCGA Provisional datasets?","p":["We renamed TCGA Provisional datasets to TCGA Firehose Legacy to better reflect that this data comes from a legacy processing pipeline. The exact same data is now available in TCGA Firehose Legacy studies."]},{"i":"what-are-tcga-firehose-legacy-datasets-and-how-do-they-compare-to-the-publication-associated-datasets-and-the-pancancer-atlas-datasets","l":"What are TCGA Firehose Legacy datasets and how do they compare to the publication-associated datasets and the PanCancer Atlas datasets?","p":["The Firehose Legacy dataset (formerly Provisional datasets) for each TCGA cancer type contains all data available from the Broad Firehose. The publication datasets reflect the data that were used for each of the publications. The samples in a published dataset are usually a subset of the firehose legacy dataset, since manuscripts were often written before TCGA completed their goal of sequencing 500 tumors.","There can be differences between firehose legacy and published data. For example, the mutation data in the publication usually underwent more QC, and false positives might have been removed or, in rare cases, false negatives added. RNA-Seq and copy-number values may also differ slightly, as different versions of analysis pipelines could have been used. Additionally, due to additional curation during the publication process, the clinical data for the publication may be of higher quality or may contain a few more data elements, sometimes derived from the genomic data (e.g., genomic subtypes).","The TCGA PanCancer Atlas datasets derive from an effort to unify TCGA data across all tumor types. Publications resulting from this effort can be found at the TCGA PanCancer Atlas site. In the cBioPortal, data from the PanCancer Atlas is divided by tumor type, but these studies have uniform clinical elements, consistent processing and normalization of mutations, copy number, mRNA data and are ideally processed for comparative analyses."]},{"i":"where-do-the-thresholded-copy-number-call-in-tcga-firehose-legacy-data-come-from","l":"Where do the thresholded copy number call in TCGA Firehose Legacy data come from?","p":["Thresholded copy number calls in the TCGA Firehouse Legacy datasets are generated by the GISTIC 2.0 algorithm and obtained from the Broad Firehose."]},{"i":"which-studies-have-mutsig-and-gistic-results-how-do-these-results-compare-to-the-data-in-the-tcga-publications","l":"Which studies have MutSig and GISTIC results? How do these results compare to the data in the TCGA publications?","p":["MutSig and GISTIC results about the statistical significance of recurrence of mutations and copy-number alterations in specific genes are available for many TCGA studies. The MutSig and GISTIC results reported in cBioPortal are based on the same mutations and copy number data reported in each TCGA publication, or the Broad Firehose for the firehose legacy data sets. However, the publication may or may not have included the complete MutSig and GISTIC output, and therefore there may be some discrepancies between the publication and the data in cBioPortal."]},{"i":"how-can-i-download-the-pancancer-atlas-data","l":"How can I download the PanCancer Atlas data?","p":["PanCancer Atlas data can be downloaded on a study-by-study basis from cBioPortal through the Datasets page or our DataHub. To download all cancer types together, try the Genomic Data Commons PanCancer Atlas page."]},{"i":"dna-mutations-copy-number--fusions","l":"DNA (Mutations, Copy Number & Fusions)"},{"i":"does-the-cbioportal-contain-synonymous-mutation-data","l":"Does the cBioPortal contain synonymous mutation data?","p":["No, the cBioPortal does not currently support synonymous mutations. This may change in the future, but we have no plans yet to add this feature."]},{"i":"what-processing-or-filtering-is-applied-to-generate-the-mutation-data","l":"What processing or filtering is applied to generate the mutation data?","p":["Within cBioPortal, we utilize the mutation calls as provided by each publication. We do not perform any additional filtering. The only processing we do is to standardize the annotation of the mutations using Genome Nexus(which utilizes VEP with the canonical MSKCC transcript). Read more about the transcript assignments here. For specifics of which tools were used to call mutations and filters that may have been applied, refer to the publication manuscript."]},{"i":"what-transcripts-are-used-for-annotating-mutations","l":"What transcripts are used for annotating mutations?","p":["Prior to loading a study into cBioPortal, we run all mutation data through a standard pipeline (see above), which re-annotates all mutations to the canonical MSKCC transcript. Read more about the transcript assignments here."]},{"i":"how-are-protein-domains-in-the-mutational-lollipop-diagrams-specified","l":"How are protein domains in the mutational lollipop diagrams specified?","p":["Protein domain definitions come from PFAM."]},{"i":"what-is-the-difference-between-a-splice-site-mutation-and-a-splice-region-mutation","l":"What is the difference between a “splice site” mutation and a “splice region” mutation?","p":["A “splice site” mutation occurs in an intron, in a splice acceptor or donor site (2bp into an intron adjacent to the intron/exon junction), defined by Sequence Ontology. “Splice region” mutations are mutations that occur near the intron/exon junction, defined by Sequence Ontology. While synonymous mutations are generally excluded from cBioPortal, these “splice region” synonymous mutations are included due to their potential impact on splicing."]},{"i":"what-do-amplification-gain-deep-deletion-shallow-deletion-and--2--1-0-1-and-2-mean-in-the-copy-number-data","l":"What do “Amplification”, “Gain”, “Deep Deletion”, “Shallow Deletion” and \"-2\", \"-1\", \"0\", \"1\", and \"2\" mean in the copy-number data?","p":["These levels are derived from copy-number analysis algorithms like GISTIC or RAE, and indicate the copy-number level per gene:","-2 or Deep Deletion indicates a deep loss, possibly a homozygous deletion","-1 or Shallow Deletion indicates a shallow loss, possibley a heterozygous deletion","0 is diploid","1 or Gain indicates a low-level gain (a few additional copies, often broad)","2 or Amplification indicate a high-level amplification (more copies, often focal)","Note that these calls are putative. We consider the deep deletions and amplifications as biologically relevant for individual genes by default. Note that these calls are usually not manually reviewed, and due to differences in purity and ploidy between samples, there may be false positives and false negatives."]},{"i":"what-is-gistic-what-is-rae","l":"What is GISTIC? What is RAE?","p":["Copy number data sets within the portal are often generated by the GISTIC or RAE algorithms. Both algorithms attempt to identify significantly altered regions of amplification or deletion across sets of patients. Both algorithms also generate putative gene/patient copy number specific calls, which are then input into the portal.","For TCGA studies, the table in allthresholded.bygenes.txt (which is the part of the GISTIC output that is used to determine the copy-number status of each gene in each sample in cBioPortal) is obtained by applying both low- and high-level thresholds to to the gene copy levels of all the samples. The entries with value +/- 2 exceed the high-level thresholds for amplifications/deep deletions, and those with +/- 1 exceed the low-level thresholds but not the high-level thresholds. The low-level thresholds are just the 'ampthresh' and 'delthresh' noise threshold input values to GISTIC (typically 0.1 or 0.3) and are the same for every thresholds.","By contrast, the high-level thresholds are calculated on a sample-by-sample basis and are based on the maximum (or minimum) median arm-level amplification (or deletion) copy number found in the sample. The idea, for deletions anyway, is that this level is a good approximation for hemizygous losses given the purity and ploidy of the sample. The actual cutoffs used for each sample can be found in a table in the output file sample_cutoffs.txt. All GISTIC output files for TCGA are available at: gdac.broadinstitute.org."]},{"l":"RNA"},{"i":"does-the-portal-store-raw-or-probe-level-data","l":"Does the portal store raw or probe-level data?","p":["No, the portal only contains gene-level data. Data for different isoforms of a given gene are merged. Raw and probe-level data for data sets are available via NCBI GEO, dbGaP or through the GDC. See the cancer type description on the main query page or refer to the original publication for links to the raw data."]},{"i":"what-are-mrna-and-microrna-z-scores","l":"What are mRNA and microRNA Z-Scores?","p":["For mRNA and microRNA expression data, we typically compute the relative expression of an individual gene in a tumor sample to the gene's expression distribution in a reference population of samples. That reference population is all profiled samples (by default for mRNA), or normal samples (when specified), or all samples that are diploid for the gene in question (discontinued). The returned value indicates the number of standard deviations away from the mean of expression in the reference population (Z-score). The normalization method is described here. Please note that the expression results by querying a gene with the default setting (z-score threshold of 2) oftentimes are not meaningful. Since the z-scores were usually calculated compared to other tumor samples, high or low expression does not necessarily mean that the gene is expressed irregularly in tumors. The data is useful for correlation analysis, for example, pick a threshold based on overall expression (using Plots tab) and compare survival data between expression high and low groups."]},{"i":"is-there-any-normal-rna-seq-data-in-cbioportal","l":"Is there any normal RNA-seq data in cBioPortal?","p":["We have RNASeqV2 mRNA expression data for normal samples of 16 TCGA PanCan Atlas Cohorts. The data was curated from GDC, and can be downloaded from our Datahub or Data Set page. This data is not directly queriable in portal; they are only used as reference data for calculating the \"relavtive to normal expression z-score\" profile. Example: ERBB2 expression z-scores relative to normal expression."]},{"i":"how-is-tcga-rnaseqv2-processed-what-units-are-used","l":"How is TCGA RNASeqV2 processed? What units are used?","p":["RNASeqV2 from TCGA is processed and normalized using RSEM. Specifically, the RNASeq V2 data in cBioPortal corresponds to the rsem.genes.normalized_results file from TCGA. A more detailed explanation of RSEM output can be found here. cBioPortal then calculates z-scores as described above in What are mRNA and microRNA Z-Scores?"]},{"i":"is-there-microrna-data","l":"Is there microRNA data?","p":["We have microRNA data for only a few studies and they are not up to date. To download more updated miRNA data, please go to either Broad Firehose, or GDC."]},{"i":"how-can-i-query-micrornas-in-the-portal","l":"How can I query microRNAs in the portal?","p":["You can input either precursor or mature miRNA IDs. Since one precursor ID may correspond to multiple mature IDs and vise versa, the portal creates one internal ID for each pair of precursor ID and mature ID mapping. For example, an internal ID of MIR-29B-1/29B stands for precursor microRNA hsa-mir-29b-1 and mature microRNA hsa-miR-29b. After entering a precursor or mature ID, you will be asked to select one internal ID for query and that internal ID will also be displayed in the Oncoprint."]},{"l":"Protein"},{"i":"how-can-i-query-phosphoprotein-levels-in-the-portal","l":"How can I query phosphoprotein levels in the portal?","p":["You need to input special IDs for each phosphoprotein/phopshosite such as AKT1_pS473 (which means AKT1 protein phosphorylated at serine residue at position 473). You could also input aliases such as phosphoAKT1 or phosphoprotein, and the portal will ask you to select the phosphoprotein/phosphosite of your interest. Note that phosphoprotein data is only available for select studies and for a limited number of proteins / phosphorylation sites."]},{"i":"why-isnt-there-protein-data-for-my-gene-of-interest","l":"Why isn’t there protein data for my gene of interest?","p":["Most of the protein expression data in cBioPortal comes from assays like RPPA which only interrogate a subset of all proteins. TCGA ovarian, breast, and colorectal firehose legacy studies also have mass-spectrometry-based proteomics data from CPTAC which cover more genes/proteins."]},{"l":"DNA Methylation"},{"i":"which-methylation-probe-is-used-for-genes-with-multiple-probes","l":"Which methylation probe is used for genes with multiple probes?","p":["For genes with multiple probes (usually from the Infinium arrays), we only include methylation data from the probe with the strongest negative correlation between the methylation signal and the gene's expression in the study (TCGA only)."]},{"l":"Clinical Data"},{"i":"what-kind-of-clinical-data-is-stored-in-the-portal","l":"What kind of clinical data is stored in the portal?","p":["The portal currently stores de-identified clinical data, such as gender, age, tumor type, tumor grade, overall and disease-free survival data, when available. The available clinical data will differ from study to study."]},{"i":"what-is-the-meaning-of-os_status--os_months-and-pfs_status--pfs_months","l":"What is the meaning of OS_STATUS / OS_MONTHS, and PFS_STATUS / PFS_MONTHS?","p":["OS_STATUS means overall survival status (\"0\" -> \"living\" or \"1\" -> \"deceased\") and OS_MONTHS indicates the number of months from time of diagnosis to time of death or last follow up. PFS refers to “progression free survival”, indicating whether patient’s disease has recurred/progressed (PFS_STATUS), and at what time the disease recurred or the patient was last seen (PFS_MONTHS)."]},{"l":"Analysis Questions"},{"i":"how-can-i-queryexplore-a-select-subset-of-samples","l":"How can I query/explore a select subset of samples?","p":["cBioPortal allows you to run a query or explore study view using a user-specified list of samples/patients.","The first step is to define your sample set. There are two slightly different approaches you can take to defining your sample set, depending on whether you are selecting based on a positive criteria (samples with TP53 mutations) or a negative criteria (samples without a KRAS mutation).","Let’s take the positive criteria example first. Run a query for TP53 mutations using OQL (TP53: MUT) in your study of interest. Click over to the “Download” tab. In the table at the top, find the row that starts with “Samples affected”, and either Copy or Download that list. This is your list of samples that have a TP53 mutation.","Now for the negative criteria example. This also begins by using OQL to run a query for KRAS mutations (KRAS: MUT) in your study of interest. Click over to the “Download” tab. Look at the table at the top again, but this time find the row that starts with “Sample matrix”. Copy or download this data and open it in Excel. You will see a two column table that indicates whether a given sample is altered or not, indicated by 0 or 1. Sort by the second column and then copy all the sample IDs from the first column that have a 0 in the second column. This is your list of samples that do not have a KRAS mutation.","With a sample list in hand, you can now either run a query in just the selected samples (select “User-defined Case List” in the “Select Patient/Case Set:” dropdown) or explore this set of patients in study view (click “Select cases by IDs” and then create a Virtual Study restricted to just those samples).","For more information about OQL, see the specification page or view the tutorial slides. For more information about virtual studies, read this FAQ or view the tutorial slides."]},{"i":"how-can-i-compare-two-or-more-subsets-of-samples","l":"How can I compare two or more subsets of samples?","p":["cBioPortal has a suite of analysis tools to enable comparisons between user-defined groups of samples/patients. For an overview of this functionality, see our tutorial on group comparison."]},{"i":"is-it-possible-to-determine-if-a-particular-mutation-is-heterozygous-or-homozygous-in-a-sample-when-a-sample-has-2-mutations-in-one-gene-is-it-possible-to-determine-whether-the-mutations-are-in-cis-or-in-trans-with-each-other","l":"Is it possible to determine if a particular mutation is heterozygous or homozygous in a sample? When a sample has 2 mutations in one gene, is it possible to determine whether the mutations are in cis or in trans with each other?","p":["There is currently no way to definitively determine whether a mutation is heterozygous/homozygous or in cis/trans with another mutation. However, you can try to infer the status of mutations by noting the copy number status of the gene and the variant allele frequency of the mutation(s) of interest relative to other mutations in the same sample. The cBioPortal patient/sample view can help you accomplish this.","Specifically in the case of TCGA samples with two mutations in the same gene, you can also obtain access to the aligned sequencing reads from the GDC and check if the mutations are in cis or in trans (if the mutations are close enough to each other)."]},{"i":"how-can-i-query-overunder-expression-of-a-gene","l":"How can I query over/under expression of a gene?","p":["cBioPortal supports Onco Query Language (OQL) which can be used to query over/under expression of a gene. When writing a query, select an mRNA expression profile. By default, samples with expression z-scores >2 or <-2 in any queried genes are considered altered. Alternate cut-offs can be defined using OQL, for example: \"EGFR: EXP>2\" will query for samples with an EGFR expression z-score >2. Review for the OQL specification page or tutorial slides for more specifics and examples."]},{"i":"how-can-i-compare-outcomes-in-patients-with-high-vs-low-expression-of-a-gene","l":"How can I compare outcomes in patients with high vs low expression of a gene?","p":["To compare outcomes in patients with high vs low expression of a gene (excluding those patients with intermediate levels of expression), we will follow a 2 step process that builds on the approach described above in How can I query/explore a select subset of samples?, utilizing OQL to first identify and then stratify that cases of interest.","First, identify the sample set using OQL. For example, to stratify patients based on expression of EGFR, add an mRNA profile to the query, and write \"EGFR: EXP>2 EXP<-2\" in the gene set box. After running the query, go to the Download tab and copy/download the “Samples affected” list.","Second, return to the homepage and paste the list of sample IDs from the previous step into the “User-defined Case List” in the “Select Patient/Case Set:” dropdown. This query will now only look at samples with high or low expression. To now stratify into high vs low for survival analysis, enter \"EGFR: EXP>2\" in the gene set box (don’t forget to select the same mRNA profile). Run the query and click over to the Survival tab. The “cases with alteration” are patients with high expression of EGFR and the cases without alteration are those with low expression of EGFR.","We use 2 and -2 as example thresholds above, but it is also a good idea to look at the distribution of expression data and select a threshold based on that. Plots tab can be useful for analyzing the expression distribution."]},{"l":"Results View"},{"l":"OncoPrint"},{"i":"what-are-oncoprints","l":"What are OncoPrints?","p":["OncoPrints are compact means of visualizing distinct genomic alterations, including somatic mutations, copy number alterations, and mRNA expression changes across a set of cases. They are extremely useful for visualizing gene set and pathway alterations across a set of cases, and for visually identifying trends, such as trends in mutual exclusivity or co-occurrence between gene pairs within a gene set. Individual genes are represented as rows, and individual cases or patients are represented as columns.","image"]},{"i":"can-i-change-the-order-of-genes-in-the-oncoprint","l":"Can I change the order of genes in the OncoPrint?","p":["By default, the order of genes in the OncoPrint will be the same as in your query. You can change the order by (a) clicking on the gene name and dragging it up/down or (b) clicking on the three vertical dots next to the gene name to move the gene up/down."]},{"i":"can-i-visualize-my-own-data-within-an-oncoprint","l":"Can I visualize my own data within an OncoPrint?","p":["Yes, check out the OncoPrinter tool on our Visualize Your Data page."]},{"i":"why-are-some-samples-not-profiled-for-certain-genes","l":"Why are some samples “Not profiled” for certain genes?","p":["Some studies include data from one or more targeted sequencing platforms which do not include all genes. For samples sequenced on these smaller panels, cBioPortal will indicate that a particular gene was not included on the sequencing panel used for that sample. Alteration frequency calculations for each gene also take this information into account. Hover over a sample in OncoPrint to see the gene panel name, and click on that gene panel name to view a list of the genes included on that panel."]},{"l":"Other pages"},{"i":"does-the-mutual-exclusivity-tab-calculate-its-statistics-using-all-samplesalterations-or-only-a-specific-subset","l":"Does the Mutual Exclusivity tab calculate its statistics using all samples/alterations or only a specific subset?","p":["The calculations on the Mutual Exclusivity tab are performed using all samples included in the query. A sample is defined as altered or unaltered for each gene based on the OQL utilized in the query - by default, this will be non-synonymous mutations, fusions, amplifications and deep deletions."]},{"i":"what-are-the-values-of-the-box-and-whiskers-in-a-boxplot","l":"What are the values of the box and whiskers in a boxplot?","p":["In boxplots on cBioPortal, the box is drawn from the 25th percentile (Q1) to the 75th percentile (Q3), with the horizontal line in between representing the median. Whiskers are drawn independently above and below the box, and will extend to the maximum or minimum data values, unless there are outlier values, in which case the whisker will extend to 1.5 * IQR (interquartile range = Q3-Q1). Outliers are defined as values that extend beyond 1.5 * IQR."]},{"l":"Study View"},{"i":"how-to-use-filter-in-the-url-of-study-view-page","l":"How to use filter in the URL of Study View page?","p":["You can filter the study based on values of one attribute in the URL. For example, https://www.cbioportal.org/study/summary?id=msk_impact_2017#filterJson={clinicalDataFilters:[{attributeId:CANCER_TYPE,values:[{value:Melanoma}]}]}","filterJson is set in the url hash string. Here are the allowed parameters and format for it in filterJson:"]},{"i":"what-if-i-have-other-questions-or-comments","l":"What if I have other questions or comments?","p":["Please contact us at cbioportal@googlegroups.com. Previous discussions about cBioPortal are available on the user discussion mailing list."]}],[{"l":"Overview"},{"l":"Overview of Resources"},{"l":"Tutorial Slides","p":["These tutorial slides contain annoted screenshots to walk you through using the cBioPortal site.","Single Study Exploration Google slides| PDF","Single Study Query Google slides| PDF","Patient View Google slides| PDF","Virtual Studies Google slides| PDF","Onco Query Language (OQL) Google slides| PDF","Group Comparison Google slides| PDF","Pathways Google slides| PDF"]},{"l":"Webinar Recordings","p":["Recordings of live webinars from April & May 2020","Introduction to cBioPortal youtube.com| bilibili.com | Download PDF | View slides","Mutation Details & Patient View youtube.com| bilibili.com | Download PDF | View slides","Expression Data Analysis youtube.com| bilibili.com | Download PDF | View slides","Group Comparison youtube.com| bilibili.com | Download PDF | View slides","API & R Client youtube.com| bilibili.com | Download PDF | View slides | Workshop code"]},{"l":"How-To Videos","p":["Short videos that show how to perform specific analyses or how to use specific pages.","Comparing samples based on expression level of a gene youtube.com","Proteomic profiles in cBioPortal - An example based on cancer cell lines from the Cancer Cell Line Encyclopedia (CCLE) youtube.com","Filtering and adding clinical data to Mutations tab youtube.com","Exploring the longitudinal evolution of individual patients youtube.com","Using Onco Query Language (OQL) to query based on the expression level of genes youtube.com","How to explore the data in a study youtube.com","How to run a query for genes of interest youtube.com","How to download data youtube.com","Navigating AACR GENIE - Biopharma Collaborative (BPC) dataset youtube.com"]},{"l":"Documentation","p":["Frequently Asked Questions FAQ","Onco Query Language OQL"]},{"l":"Publications","p":["Cerami et al. Cancer Discovery 2012 PubMed","Gao et al. Science Signaling 2013 PubMed"]},{"l":"Tutorials by others","p":["cBioPortal Tutorial Series by Jackson Laboratory youtube.com","Using the Cancer Digital Slide Archive in cBioPortal by Nicole M. Rivera Acevedo youtube.com (English)| youtube.com (Spanish)","Visualizing and Downloading RNASeq data from cBioPortal by Farhan Haq youtube.com"]}],[{"l":"By page"},{"l":"Resources by Page"},{"l":"Study View","p":["Tutorial Slides: Single Study Exploration Google slides| PDF","Webinar: Introduction to cBioPortal youtube.com| bilibili.com","How-To Video: Comparing samples based on expression level of a gene youtube.com","Tutorial Slides: Virtual Studies Google slides| PDF"]},{"l":"Group Comparison","p":["Tutorial Slides: Group Comparison Google slides| PDF","Webinar: Group Comparison youtube.com| bilibili.com","How-To Video: Comparing samples based on expression level of a gene youtube.com"]},{"i":"running-a-query--results-view","l":"Running a Query / Results View"},{"l":"General","p":["Tutorial Slides: Single Study Query Google slides| PDF","Webinar: Introduction to cBioPortal youtube.com| bilibili.com"]},{"l":"OQL","p":["Documentation OQL","Tutorial Slides: Onco Query Language (OQL) Google slides| PDF","Webinar: Expression Data Analysis youtube.com| bilibili.com","How-To Video: Using Onco Query Language (OQL) to query based on the expression level of genes youtube.com"]},{"l":"OncoPrint","p":["Tutorial Slides: Single Study Query Google slides| PDF","Webinar: Introduction to cBioPortal youtube.com| bilibili.com"]},{"l":"Cancer Types Summary","p":["Tutorial Slides: Single Study Query Google slides| PDF","Webinar: Introduction to cBioPortal youtube.com| bilibili.com"]},{"l":"Mutual Exclusivity","p":["Tutorial Slides: Single Study Query Google slides| PDF","Webinar: Introduction to cBioPortal youtube.com| bilibili.com"]},{"l":"Plots","p":["Tutorial Slides: Single Study Query Google slides| PDF","Webinar: Introduction to cBioPortal youtube.com| bilibili.com"]},{"l":"Mutations","p":["Tutorial Slides: Single Study Query Google slides| PDF","Webinar: Introduction to cBioPortal youtube.com| bilibili.com","Webinar: Mutation Details & Patient View youtube.com| bilibili.com","How-To Video: Filtering and adding clinical data to Mutations tab youtube.com"]},{"l":"Co-expression","p":["Tutorial Slides: Single Study Query Google slides| PDF","Webinar: Introduction to cBioPortal youtube.com| bilibili.com"]},{"i":"comparisonsurvival","l":"Comparison/Survival","p":["Tutorial Slides: Single Study Query Google slides| PDF","Webinar: Introduction to cBioPortal youtube.com| bilibili.com","Tutorial Slides: Group Comparison Google slides| PDF","Webinar: Group Comparison youtube.com| bilibili.com"]},{"l":"CN Segments","p":["Tutorial Slides: Single Study Query Google slides| PDF","Webinar: Introduction to cBioPortal youtube.com| bilibili.com"]},{"l":"Pathways","p":["Tutorial Slides: Pathways Google slides| PDF","Tutorial Slides: Single Study Query Google slides| PDF","Webinar: Introduction to cBioPortal youtube.com| bilibili.com"]},{"l":"Downloads","p":["Tutorial Slides: Single Study Query Google slides| PDF","Webinar: Introduction to cBioPortal youtube.com| bilibili.com"]},{"l":"Patient View","p":["Tutorial Slides: Patient View Google slides| PDF","Tutorial Slides: Pathways Google slides| PDF","Webinar: Introduction to cBioPortal youtube.com| bilibili.com","Webinar: Mutation Details & Patient View youtube.com| bilibili.com","How-To Video: Exploring the longitudinal evolution of individual patients youtube.com"]}],[{"i":"onco-query-language-oql","l":"Onco Query Language (OQL)"},{"l":"Introduction to OQL","p":["The Onco Query Language (OQL) is used to define which specific types of alterations are included in a query on the cBioPortal for Cancer Genomics. By default, querying for a gene includes mutations, fusions, amplifications and deep deletions. OQL can be used to specify specific mutations (e.g. BRAF V600E) or types of mutations (e.g. BRCA1 truncating mutations), lower level copy number alterations (e.g. CDKN2A shallow deletions), changes in mRNA or protein expression, and more.","OQL-specified alterations will be reflected on most tabs, including OncoPrint, but are not currently reflected on the Plots, Co-Expression or Expression tabs.","Note that OQL assumes any word that it doesn't recognize is a mutation code.","Additional explanation and examples using OQL are available in the User Guide."]},{"l":"OQL Keywords","p":["* These are the default OQL keywords used for each data type when a gene is queried without any explicit OQL.","AMP Amplifications HOMDEL Deep Deletions GAIN Gains HETLOSS Shallow Deletions Comparison operators can also be used with CNA(e.g. CNA = GAIN is the same as AMP GAIN)","AMP HOMDEL","Copy Number Alterations","Data Type","Default*","EXP -x mRNA expression is less than x standard deviations (SD) below the mean EXP x mRNA expression is greater than x SD above the mean The comparison operators = and = also work","EXP = 2 EXP = -2","FUSION","FUSION All fusions (note that many studies lack fusion data)","Fusions","Keywords and Syntax","mRNA Expression","MUT","MUT All non-synonymous mutations MUT = protein change Specific amino acid changes (e.g. V600E or V600) MUT = mutation type Acceptable values are: MISSENSE, NONSENSE, NONSTART, NONSTOP, FRAMESHIFT, INFRAME, SPLICE, TRUNC","Mutations","PROT -x Protein expression is less than x standard deviations (SD) below the mean PROT x Protein expression is greater than x SD above the mean The comparison operators = and = also work","PROT = 2 PROT = -2","Protein/phosphoprotein level","Users can define specific subsets of genetic alterations for five data types:"]},{"l":"OQL modifiers","p":["Mutations and copy number alterations can be further refined using modifiers:","Keyword","Applicable Data Type","Explanation","DRIVER","Mutations Fusions Copy Number Alterations","Include only mutations, fusions and copy number alterations which are driver events, as defined in OncoPrint (default: OncoKB and CancerHotspots).","GERMLINE","Mutations","Include only mutations that are defined as germline events by the study.","SOMATIC","Include all mutations that are not defined as germline.","(a-b)(protein position range)","Include all mutations that overlap with the protein position range a-b, where a and b are integers. If you add a *(i.e. (a-b*)) then it will only include those mutations that are fully contained inside a-b. The open-ended ranges (a-) and (-b) are also allowed."]},{"l":"Basic Usage","p":["When querying a gene without providing any OQL specifications, cBioPortal will default to these OQL terms for a query with Mutation and Copy Number selected in the Genomic Profiles section: MUT FUSION AMP HOMDEL","image of basic query","You can see the OQL terms applied by hovering over the gene name in OncoPrint:","image of basic query oncoprint","If you select RNA and/or Protein in the \"Genomic Profiles\" section of the query, the default settings are:","RNA: EXP = 2 EXP = -2","Protein: PROT = 2 PROT = -2","image of exp prot query oncoprint","You must select the relevant Genomic Profile in order for OQL to query that data type. For example, you can't add EXP 2 to the query without also selecting an RNA profile.","Proper formatting for OQL is straightforward: gene name, followed by a colon, followed by any OQL keywords and ending in a semicolon, an end-of-line, or both.","In general, any combination of OQL keywords and/or expressions can annotate any gene, and the order of the keywords is immaterial.","Below we will go into greater detail about each data type."]},{"l":"Mutations","p":["For example, to view TP53 truncating mutations and in-frame insertions/deletions:","FRAMESHIFT","INFRAME","MISSENSE","mutation type can be one or more of:","NONSENSE","NONSTART","NONSTOP","Note that this will only work to exclude a single event. Because OQL uses 'OR' logic, excluding multiple mutations or excluding a mutation while including another mutation (e.g. BRAF: MUT=V600 MUT!=V600E) will result in querying all mutations.","OQL can also be used to exclude a specific protein change, position or type of mutation. For example, below are examples to query all EGFR mutations except T790M, all BRAF mutations except those at V600 and all TP53 mutations except missense:","OQL for mutations can also be written without MUT =. The following examples are identical:","Or all mutations of a specific type:","SPLICE","To view cases with specific mutations, provide the specific amino acid change of interest:","TRUNC","You can also view all mutations at a particular position:"]},{"l":"Copy Number Alterations","p":["To view cases with specific copy number alterations, provide the appropriate keywords for the copy number alterations of interest. For example, to see amplifications:","Or amplified and gained cases:","Which can also be written as:"]},{"l":"Expression","p":["High or low mRNA expression of a gene is determined by the number of standard deviations (SD) from the mean. For example, to see cases where mRNA for CCNE1 is greater than 3 SD above the mean:"]},{"l":"Protein","p":["High or low protein expression is similarly determined by the number of SD from the mean. For example, to see cases where protein expression is 2 SD above the mean:","Protein expression can also be queried at the phospho-protein level:"]},{"l":"Modifiers","p":["Modifiers can be used on their own or in combination with other OQL terms for mutations, fusions and copy number alterations to further refine the query. Modifiers can be combined with other OQL terms using an underscore. The order in which terms are combined is immaterial."]},{"l":"Driver","p":["The DRIVER modifier applies to mutations, fusions and copy number alterations. The definition of what qualifies as a driver alteration comes from the \"Mutation Color\" menu in OncoPrint. By default, drivers are defined as mutations, fusions and copy number alterations in OncoKB or CancerHotspots.","On its own, the DRIVER modifier includes driver mutations, fusions and copy number alterations:","Or it can be used in combination with another OQL term. For example, to see only driver fusion events:","Or driver missense mutations:","When combining DRIVER with another OQL term, the order doesn't matter: MUT_DRIVER and DRIVER_MUT are equivalent. DRIVER can be combined with:","MUT","MUT = mutation type or MUT = protein change","FUSION","CNA","AMP or GAIN or HETLOSS or HOMDEL","GERMLINE or SOMATIC(see below)"]},{"i":"germlinesomatic","l":"Germline/Somatic","p":["The GERMLINE and SOMATIC modifiers only apply to mutations. A mutation can be explicitly defined as germline during the data curation process. Note that very few studies on the public cBioPortal contain germline data.","GERMLINE or SOMATIC can be combined with:","MUT","MUT = mutation type or MUT = protein change","DRIVER","To see all germline BRCA1 mutations:","Or to see specifically truncating germline mutations:","The order is immaterial; both options produce identical results.","Or to see somatic missense mutations:","GERMLINE or SOMATIC can also be combined with DRIVER and, optionally, a more specific mutation term (e.g. NONSENSE):"]},{"l":"The DATATYPES Command","p":["To save copying and pasting, the DATATYPES command sets the genetic annotation for all subsequent genes. Thus,","is equivalent to:"]},{"l":"Merged Gene Tracks","p":["OQL can be used to create a merged gene track in OncoPrint, in which alterations in multiple genes appear as a single track. This is done by enclosing a list of genes in square brackets. By default, the track will be labeled by the gene names, separated by '/'. To instead specify a label, type the desired label within double quotes at the beginning of the square brackets. For example:","The resulting merged gene track will be visible in OncoPrint and can be expanded to view the individual gene tracks. For example:","Image of merged genes in OncoPrint","https://www.cbioportal.org/results/oncoprint?session_id=5c1966e2e4b05228701f958e","It is possible to include OQL for specific alterations in merged gene tracks, as well as querying a combination of single and merged gene tracks.","Note that merged gene tracks only appear in OncoPrint. All other pages show the individual genes."]},{"i":"example-rb-pathway-alterations","l":"Example: RB Pathway Alterations","p":["Provided below is one example of the power of using OQL. Additional examples are available in the User Guide."]},{"l":"Using the Defaults","p":["Select Ovarian Serous Cystadenocarcinoma (TCGA, Nature 2011) with the following data types:","Mutations","Putative copy-number alterations (GISTIC)","mRNA expression (mRNA expression Z-scores (all genes))","Input the following three genes in the RB pathway:","CCNE1","RB1","CDKN2A","image of rb query","Submit this query and note how many samples have alterations in multiple of these genes:","image of rb oncoprint","https://www.cbioportal.org/results/oncoprint?session_id=5c1966cee4b05228701f958d"]},{"l":"Greater Insight with OQL","p":["Given what is known about the RB pathway, the events that are most likely selected for in the tumors are CCNE1 amplification, RB1 deletions or mutations, and loss of expression of CDKN2A. To investigate this hypothesis, we can use OQL to display only these events. Modify the query to reflect this:","Examine the updated OncoPrint:","image of modified rb oncoprint","https://www.cbioportal.org/results/oncoprint?session_id=5c1966aee4b05228701f958c","This shows that alterations in these genes are almost entirely mutually-exclusive -- no cases are altered in all three genes and only six are altered in two genes. This supports the theory that the tumor has selected for these events."]},{"i":"questions-feedback","l":"Questions? Feedback?","p":["Please share any questions or feedback on OQL with us: https://groups.google.com/group/cbioportal","Also note that additional explanation and examples using OQL are available in the User Guide."]}],[{"l":"News"},{"i":"aug-21-2023","l":"Aug 21, 2023","p":["Added data consisting of 4,488 samples from 7 studies:","Lung Adenocarcinoma Met Organotropism (MSK, Cancer Cell 2023) 2653 samples","Acute Myeloid Leukemia (OHSU, Cancer Cell 2022) 942 samples","Colon Cancer (Sidra-LUMC AC-ICAM, Nat Med 2023) 348 samples","Pediatric Neuroblastoma (MSK, Nat Genet 2023) 223 samples","Colorectal Adenocarcinoma (MSK, Nat Commun 2022) 180 samples","Bladder Cancer (Columbia University/MSK, Cell 2018) 130 samples","Myoepithelial Carcinomas of Soft Tissue (WCM, CSH Molecular Case Studies 2022) 12 samples","Gene Tables Update Updated tables of genes (main and alias), based on Apr 1, 2023 HGNC release. See seedDB release note here for details."]},{"i":"aug-1-2023","l":"Aug 1, 2023","p":["Enhancement: One-sided Fisher's exact tests were changed to be two-sided. The affected pages are:","Results View Page - Mutual Exclusivity Tab","Results View Page - Comparison Tab - Genomic Alterations Tab","Comparison Page - Genomic Alterations Tab","Comparison Page - Mutations Tab","Please note that the Mutations tab on the Comparison page is a recent feature and was introduced with the two-sided Fisher's exact test already implemented.","Several users pointed out that using a one-sided test was incorrect for these comparisons. Please see discussions here for more information."]},{"i":"may-2-2023","l":"May 2, 2023","p":["New Feature: The mutations tab now shows variant annotations from the repository of Variant with Unexpected Effects (reVUE)."]},{"i":"apr-11-2023","l":"Apr 11, 2023","p":["New Feature: Disable autocommit and manually commit filters in study view. Manually commit filters can improve cBioPortal performance when query large dataset."]},{"i":"apr-5-2023","l":"Apr 5, 2023","p":["Added data consisting of 2,472 samples from 5 studies:","Bladder Cancer (MSK, Cell Reports 2022) 1659 samples","Gastrointestinal Stromal Tumor (MSK, NPJ Precis Oncol 2023) 499 samples","Appendiceal Cancer (MSK, J Clin Oncol 2022) 273 samples","Colorectal Cancer (MSK, Cancer Discovery 2022) 22 samples","Nerve Sheath Tumors (Johns Hopkins, Sci Data 2020) 19 samples[First GRCh38 Study]","Data Improvement","Added TERT promoter mutation status to Melanomas (TCGA, Cell 2015), Papillary Thyroid Carcinoma (TCGA, Cell 2014) TCGA studies."]},{"i":"apr-4-2023","l":"Apr 4, 2023","p":["New Feature: Allow numeric data type for custom data charts.","This also allows to have numerical custom data after we query based on genes (custom data 2 in the image):"]},{"i":"jan-10-2023","l":"Jan 10, 2023","p":["New Feature: New Pathways tab on the Group Comparison view. Example: Primary vs Metastasis samples in MSK-IMPACT Clinical Sequencing Cohort"]},{"i":"dec-13-2022","l":"Dec 13, 2022","p":["New Feature: New Mutations tab on the Group Comparison view. Example: Primary vs Metastasis samples in MSK-IMPACT Clinical Sequencing Cohort"]},{"i":"oct-12-2022","l":"Oct 12, 2022","p":["Added data consisting of 1,459 samples from 10 studies:","Hepatocellular Carcinoma (MERiC/Basel, Nat Commun. 2022) 122 samples","Prostate Cancer Brain Metastases (Bern, Nat Commun. 2022) 168 samples","Pan-Cancer MSK-IMPACT MET Validation Cohort (MSK 2022) 69 samples","Endometrial Carcinoma cfDNA (MSK, Clin Cancer Res 2022) 44 samples","Endometrial Carcinoma MSI (MSK, Clin Cancer Res 2022) 181 samples","Gallbladder Cancer (MSK, Clin Cancer Res, 2022) 244 samples","Meningioma (University of Toronto, Nature 2021) 121 samples","Mixed Tumors: Selpercatinib RET Trial (MSK, Nat Commun. 2022) 188 samples","Low-Grade Serous Ovarian Cancer (MSK, Clin Cancer Res 2022) 119 samples","Urothelial Carcinoma (BCAN/HCRN 2022) 203 samples"]},{"i":"sep-6-2022","l":"Sep 6, 2022","p":["Enhancement: Oncoprint can now save clinical tracks after login"]},{"i":"aug-11-2022","l":"Aug 11, 2022","p":["New Major Release: v5.0.0 release drops support for fusions in the mutation data format. Going forward fusions can only be imported in the Structural Variant (SV) format. This is mainly a refactoring effort to simplify the codebase and pave the way for the development of novel structural variant visualizations in the future. For cBioPortal instance maintainer, please reference our Migration Guide for instruction."]},{"i":"jul-26-2022","l":"Jul 26, 2022","p":["Added data consisting of 6,631 samples from 7 studies:","Metastatic Biliary Tract Cancers (SUMMIT - Neratinib Basket Trial, 2022) 36 samples","Rectal Cancer (MSK, Nature Medicine 2022) 801 samples","Lung Adenocarcinoma (MSK Mind,Nature Cancer 2022) 247 samples","Myelodysplastic Syndromes (MDS IWG, IPSSM, NEJM Evidence 2022) 3,323 samples","Esophagogastric Cancer (MSK, Clin Cancer Res 2022) 237 samples","Pan-cancer Analysis of Advanced and Metastatic Tumors (BCGSC, Nature Cancer 2020) 570 samples","Prostate Adenocarcinoma (MSK, Clin Cancer Res. 2022) 1,417 samples"]},{"i":"may-31-2022","l":"May 31, 2022","p":["New Feature: Added Quartiles, Median split and Generate bins options for bar charts on the study view page, where Generate bins allows user to define bin size and min value"]},{"i":"may-12-2022","l":"May 12, 2022","p":["New Feature: Show cohort alteration frequencies in pathways from NDEx on the Results View. Example: Glioblastoma signaling pathways in MSK-IMPACT (2017) cohort"]},{"i":"may-5-2022","l":"May 5, 2022","p":["New Feature: View mutations and copy number changes in the Integrative Genomics Viewer (IGV) on the Patient View. Example: Endometrial cancer patient in TCGA","New Feature: Add charts that plot categorical vs continuous data on the Study View. Example: MSK-IMPACT (2017) cohort","New Feature: Several single cell data integrations are now available for the CPTAC glioblastoma study, allowing one to:","Compare genomic alterations and cell type fractions in oncoprints on the Results View( Example)","Explore the single cell data further in Vitessce on the Patient View( Example)","Create cohorts and groups based on cell type fractions on the Study View( Example)","Compare differences in cell type fractions between groups on the Comparison Page( Example)"]},{"i":"apr-20-2022","l":"Apr 20, 2022","p":["Added data consisting of 2,557 samples from 5 studies:","Breast Cancer (HTAN, 2022) 5 samples","Colorectal Cancer (MSK, 2022) 47 samples","Pediatric Pancan Tumors (MSK, 2022) 135 samples","Sarcoma (MSK, 2022) 2,138 samples","Lung Cancer in Never Smokers (NCI, Nature Genetics 2021) 232 samples","Gene Tables Update Updated tables of genes (main and alias), based on Jan 1, 2022 HGNC release. See seedDB release note here for details.","Data Improvement","Pan-can studies timeline addition: TREATMENT, OTHER MALIGNANCY FORM, SAMPLE ACQUISITION, STATUS are added to all 32 TCGA Pan-Can studies. Details for data source and transformation process can be found here or in the README.md files included in each study folder on datahub. Example: patient view of TCGA-A2-A04P in Breast Invasive Carcinoma Tumor Type","Pan-can studies methylation addition: methylation profile (27k and 450k merged) are added to all 32 TCGA Pan-Can studies, in generic assay format. Data source: GDC. Example: search by gene or probe from dropdown, to add a chart in study view, a track in Oncoprint (single study query only), or plots in plots tab.","Single cell (type fraction and phases) data (in generic assay format) is added to Glioblastoma (CPTAC, Cell 2021)"]},{"i":"jan-4-2022","l":"Jan 4, 2022","p":["Added data consisting of 27,447 samples from 10 studies:","Endometrial Carcinoma (CPTAC, Cell 2020) 95 samples","Pancreatic Ductal Adenocarcinoma (CPTAC, Cell 2021) 140 samples","Lung Squamous Cell Carcinoma (CPTAC, Cell 2021) 108 samples","Lung Adenocarcinoma (CPTAC, Cell 2020) 110 samples","Glioblastoma (CPTAC, Cell 2021) 99 samples","Breast Cancer (CPTAC, Cell 2020) 122 samples","Pediatric Brain Cancer (CPTAC/CHOP, Cell 2020) 218 samples","Metastatic Prostate Cancer (Provisional, June 2021) 123 samples","MSK MetTropism (MSK, Cell 2021) 25,775 samples","Cancer Therapy and Clonal Hematopoiesis (MSK, 2021) 657 samples","Added TMB (nonsynonymous) scores for all studies. Example: new TMB field for study gbm_cptac_2021(Details for the calculation can be found HERE)"]},{"i":"nov-12-2021","l":"Nov 12, 2021","p":["Added data consisting of 3,680 samples from 6 studies:","Breast Cancer MAPK (MSKCC, Nat Commun 2021) 145 samples","Colorectal Cancer (MSK, 2020) 64 samples","Breast Cancer (MSK, Clinical Cancer Res 2020) 60 samples","High-Grade Serous Ovarian Cancer (MSK, 2021) 45 samples","Diffuse Glioma (GLASS Consortium, Nature 2019) 444 samples","Pan-cancer analysis of whole genomes (ICGC/TCGA, Nature 2020) 2,922 samples"]},{"i":"nov-32021","l":"Nov 3,2021","p":["New Feature: Add Uniprot topology as a new annotation track on the Mutations Tab of the Results View. Example: EGFR in MSK-IMPACT (2017) cohort"]},{"i":"oct-1-2021","l":"Oct 1, 2021","p":["New Feature: Arm level Copy Number events are now loaded into cBioPortal using the Categorial Generic Assay Data Type. They can be found in a tab under the Add Charts Button of the Study View Example: Arm Level Data in TCGA PanCancer Atlas"]},{"i":"sep-22-2021","l":"Sep 22, 2021","p":["Added data consisting of 14,844 samples from 7 studies:","Colorectal Cancer (MSK, Gastroenterology 2020) 471 samples","Metastatic Breast Cancer (MSK, Cancer Discovery 2021) 1,365 samples","Lung Adenocarcinoma (MSKCC, 2021) 186 samples","Race Differences in Prostate Cancer (MSK, 2021) 2,069 samples","Medulloblastoma (DKFZ, Nature 2017) 491 samples","Thoracic Cancer (MSK, 2021) 68 samples","China Pan-cancer (OrigiMed, 2020) 10,194 samples"]},{"i":"sep-21-2021","l":"Sep 21, 2021","p":["Enhancement: Dowloading the Lollipop plot on the Mutations Tab of the Results View will now also include the annotation tracks:"]},{"i":"aug-17-2021","l":"Aug 17, 2021","p":["New Feature: The Mutations Tab of the Results View can now show exon numbers as an annotation track Example: MET Exon 14 Mutations in MSK-IMPACT (2017) cohort"]},{"i":"aug-10-2021","l":"Aug 10, 2021","p":["New Feature: Use the filtering capabilities in the Mutations Tab of the Results View to create a custom cohort that one can open directly in the Study View Example: CTNNB1 in MSK-IMPACT (2017) cohort"]},{"i":"jul-27-2021","l":"Jul 27, 2021","p":["New Feature: Add a custom filter to any column of the Mutations Tab in the Results View Example: CTNNB1 in MSK-IMPACT (2017) cohort","New Feature: Show detailed descriptions for each annotation source in the header of the the Mutations Table in both the Results View and the Patient View Example link"]},{"i":"jul-6-2021","l":"Jul 6, 2021","p":["New Feature: Add any clinical data as a column on the Mutations Tab in the Results View Example: EGFR in MSK-IMPACT (2017) cohort"]},{"i":"june-23-2021","l":"June 23, 2021","p":["Added data consisting of 1,084 samples from 5 studies:","Intrahepatic Cholangiocarcinoma (MSK, Hepatology 2021) 412 samples","Intrahepatic Cholangiocarcinoma (Mount Sinai 2015) 8 samples","RAD51B Associated Mixed Cancers (Mandelker 2021 19 samples","Intrahepatic Cholangiocarcinoma (MSK, 2020) 219 samples","Lung Adenocarcinoma (NPJ Precision Oncology, MSK 2021) 426 samples","Added mass-spec proteome data from CPTAC to Breast Invasive Carcinoma (TCGA, PanCancer Atlas), Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas) and Colorectal Adenocarcinoma (TCGA, PanCancer Atlas).","Added mass-spec phosphoproteome site level expression from CPTAC to Breast Invasive Carcinoma (TCGA, PanCancer Atlas) and Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas).","Updated gene tables Updated tables of genes (main and alias), based on HGNC. See details HERE in section Contents of seed database. Sripts/resources/process used to construct new tables are described HERE."]},{"i":"june-1-2021","l":"June 1, 2021","p":["New Feature: In certain studies where we have the data we show read counts for uncalled mutations on the Patient View Example: A patient in the Glioma (MSK, 2019) cohort"]},{"i":"may-10-2021","l":"May 10, 2021","p":["New Feature: Pick color for User Defined Groups Example: Color Bladder Cancer Group in MSK-IMPACT (2017) cohort, implemented by The Hyve."]},{"i":"may-4-2021","l":"May 4, 2021","p":["New Feature: Add more categories of mutations to the Mutations Tab on the Results View, including Driver/VUS, Splice and Structural Variants Example: TP53 alterations in the MSK-IMPACT (2017) cohort"]},{"i":"april-21-2021","l":"April 21, 2021","p":["Added data consisting of 4074 samples from 9 studies:","Metaplastic Breast Cancer (MSK, 2021) 19 samples","Lung Adenocarcinoma (MSKCC, 2020) 604 samples","Cutaneous Squamous Cell Carcinoma (UCSF, 2021) 105 samples","MSK-IMPACT and MSK-ACCESS Mixed Cohort (MSK, 2021) 1446 samples","Melanoma (MSKCC, 2018) 720 samples","Cholangiocarcinoma (ICGC, Cancer Discov 2017) 489 samples","Esophageal/Stomach Cancer (MSK, 2020) 487 samples","Retinoblastoma (MSK, Cancers 2021) 83 samples","Combined Hepatocellular and Intrahepatic Cholangiocarcinoma (Peking University, Cancer Cell 2019) 121 samples"]},{"i":"april-20-2021","l":"April 20, 2021","p":["New Feature: Add driver annotations to download tab on Results View Example: RAS/RAF alterations in colorectal cancer"]},{"i":"march-30-2021","l":"March 30, 2021","p":["Enhancement: Add 95% Confidence Interval for Survival Plots Example: Altered vs Unaltered EGFR in Lung Cancer"]},{"i":"march-11-2021","l":"March 11, 2021","p":["New Feature: Combine different types of alterations in Comparison View Example: Deletions and Truncating events in primary vs metastases or read more on The Hyve's blog","Enhancement: Improve UI for OncoPrint, aggregating various data modalities in a single add track dropdown button Example: Add clinical, heatmap and treatment response data into the OncoPrint"]},{"i":"february-16-2021","l":"February 16, 2021","p":["Enhancement: Show only TCGA PanCancer Atlas Pathways in Results and Patient View to avoid showing many similar pathways Example: Clinvar APC and CTNNB1 alterations in WNT pathway"]},{"i":"january-28-2021","l":"January 28, 2021","p":["New Feature: Show ClinVar Interpretation in Mutation tables Example: Clinvar Interpretations in BRCA2"]},{"i":"january-12-2021","l":"January 12, 2021","p":["New Feature: Add your own custom data for a sample or patient to use on the study or comparison view Example: Add custom data to three samples and do a comparison","New Feature: Show the mutations of a patient inside a pathway schematic using PathwayMapper Example: Notch signaling pathway in a prostate cancer patient","New Feature: Display and compare generic assays, such as microbiome and treatment response, on the study view Example: Prasinovirus microbiome signatures in TCGA","New Feature: The Plots tab on Results View now allows you to group alterations by Driver and VUS Example: POLE driver mutations vs VUSs against mutation counts in TCGA Colorectal Adenocarcinoma"]},{"i":"december-31-2020","l":"December 31, 2020","p":["Added data consisting of 430 samples from 5 studies:","Juvenile Papillomatosis and Breast Cancer (MSK, 2020) 5 samples","Mixed cfDNA (MSKCC, 2020) 229 samples","Metastatic Melanoma (DFCI, Nature Medicine 2019) 144 samples","Lung Cancer (SMC, Cancer Research 2016) 22 samples","Upper Tract Urothelial Carcinoma (IGBMC, Genome Biology 2021) 30 samples","Added survival data to Breast Cancer (METABRIC, Nature 2012 & Nat Commun 2016)"]},{"i":"november-3-2020","l":"November 3, 2020","p":["New Feature: The map of local installations of cBioPortal is available now. Please consider registering your instance here. image","Enhancement: upgraded the Genomic Evolution tab in Patient View with timeline Example image"]},{"i":"october-20-2020","l":"October 20, 2020","p":["Enhancement: Expression tab has now been merged into the Plots tab image"]},{"i":"october-16-2020","l":"October 16, 2020","p":["Added data consisting of 25,078 samples from 5 studies:","Melanomas (TCGA, Cell 2015) 359 samples","Retinoblastoma cfDNA (MSKCC 2020) 14 samples","The Angiosarcoma Project (Provisional, July 2020) 83 samples","Bladder Cancer (MSK/TCGA, 2020) 476 samples","Cancer Therapy and Clonal Hematopoiesis (MSK, 2020) 24,146 samples","Added MSI data(MSIsensor from Mariamidze et al. 2018 and MANTIS scores from Roychowdhury et al. 2017) for all 32 TCGA PanCan Atlas Cohorts.","Added new profile“RNA-Seq V2 expression Z-scores relative to normal samples” for 16 TCGA PanCan Atlas Cohorts. The normals samples RNA-Seq V2 expression data were curated from GDC, and can be downloaded from our Datahub or Data Set page. Example: ERBB2 expression z-scores relative to normal expression","image"]},{"i":"october-13-2020","l":"October 13, 2020","p":["Enhancement: Study View now allows comparing samples with mutations or copy number alterations in different genes image","New Feature: When treatment timeline is available (e.g. in this study), Study View now allows the selection and comparison of patients treated with specific drugs, or samples sequenced pre or post specific drug treatments image"]},{"i":"september-30-2020","l":"September 30, 2020","p":["New Feature: Microbiome signature data is available for comparison now. Example: comparing colorectal subtypes for enriched microbiome signatures image"]},{"i":"september-22-2020","l":"September 22, 2020","p":["Enhancement: The timeline feature in Patient View has been refactored with an improved UI. Example image","Enhancement: Logrank p-values are now provided for all survival analysis (previously only availalbe when comparing two groups). Example"]},{"i":"august-11-2020","l":"August 11, 2020","p":["New Feature: microbiome data of TCGA samples from Poore et al. 2020 are now available for analysis in the OncoPrint and Plots tabs. Example: Orthohepadnavirus across TCGA cancers image","New Feature: You can now compare DNA Methylation data between groups using the Comparison feature. Example: Comparing DNA methylation levels between samples with high vs low BRCA1 expression image","Added data consisting of 513 samples from 3 studies:","Breast Cancer (SMC 2018) 187 samples","Germ Cell Tumors and Shared Leukemias (MSK 2020) 21 samples","Lung Adenocarcinoma (OncoSG, Nat Genet 2020) 305 samples","Added RPPA data in addition to the microbiome data for 31 TCGA Pancan studies (except LAML)"]},{"i":"july-21-2020","l":"July 21, 2020","p":["New Feature: The Mutations tab now has the option to show mutation effects for different transcripts / isoforms. Note that some annotation features are only available for the canonical isoform. example image","Enhancement: The Plots tab is now supported in multi-study queries. example image","New Feature: You can now share custom groups in the Study View example"]},{"i":"june-11-2020","l":"June 11, 2020","p":["Added data consisting of 267 samples from 2 studies:","Gastric Cancer (OncoSG, 2018) 147 samples","120 ctDNA samples added to Non-Small Cell Lung Cancer (TRACERx, NEJM & Nature 2017) 447 samples"]},{"i":"june-9-2020","l":"June 9, 2020","p":["Enhancement: using OQL to query for mutations based on a protein position range. example image","New Feature: you can now send the OncoPrint data to the OncoPrinter tool for customization. image","Enhancement: Mutational spectrum data can be downloaded from OncoPrint image"]},{"i":"june-2-2020","l":"June 2, 2020","p":["Enhancement: Pediatric cancer studies are now grouped and highlighted in the query page image"]},{"i":"may-6-2020","l":"May 6, 2020","p":["Added data consisting of 574 samples from 3 studies:","Uterine Sarcoma/Mesenchymal (MSK, Clin Cancer Res 2020) 108 samples","Metastatic castration-sensitive prostate cancer (MSK, Clin Cancer Res 2020) 424 samples","Glioblastoma (Columbia, Nat Med. 2019) 42 samples","Updated one study:","Expression data was added to The Metastatic Breast Cancer Project (Provisional, February 2020)."]},{"i":"april-24-2020","l":"April 24, 2020","p":["New Feature: Add a new chart on the Study View for selecting samples based on pre-defined case lists:"]},{"i":"april-10-2020","l":"April 10, 2020","p":["New Feature: Make cohorts on the Study View using continuous molecular profiles of one or more gene(s), such as mRNA expression, methylation, RPPA and continuous CNA. example","Combine this with the group comparison feature to compare e.g. all quartiles of expression:","New Feature: Annotate mutations using the Mutation Mapper Tool on the GRCh38 reference genome:","mutation_mapper_tool_grch38"]},{"i":"april-3-2020","l":"April 3, 2020","p":["New Feature: Extended the Comparison tab to support the comparison of altered samples per gene or alteration. This example query compares NSCLC patients with 1) both mutated and amplified EGFR, 2) mutated EGFR only, and 3) amplified EGFR only.","image"]},{"i":"march-27-2020","l":"March 27, 2020","p":["Enhancement: User selections in the Plots tab are now saved in the URL. example","New Feature: Added table of data availability per profile in the Study View. example"]},{"i":"march-20-2020","l":"March 20, 2020","p":["Enhancement: Extended Survival Analysis to support more outcome measures. example","image"]},{"i":"march-18-2020","l":"March 18, 2020","p":["Added data consisting of 1,393 samples from 3 studies:","Breast Cancer (Alpelisib plus AI, Nature Cancer 2020) 141 samples","Glioma (MSKCC, Clin Cancer Res 2019) 1,004 samples","Mixed cfDNA (MSK, Nature Medicine 2019) 248 samples"]},{"i":"march-3-2020","l":"March 3, 2020","p":["New Feature: Added Pathways tab to the Results View page, which visualizes the alteration frequencies of genes in pathways of interest. The pathways are pulled from https://www.pathwaymapper.org and shown in a read only view. One can edit these pathways in the PathwayMapper editor. For more information see the tutorial.","pathwaymapper_screenshot"]},{"i":"february-12-2020","l":"February 12, 2020","p":["Added data consisting of 1,605 samples from 3 studies:","Tumors with TRK fusions (MSK, 2019) 106 samples","Lymphoma Cell Lines (MSKCC, 2020) 34 samples","Prostate Adenocarcinoma (MSKCC, 2020) 1,465 samples"]},{"i":"february-6-2020","l":"February 6, 2020","p":["New Feature: Extend the recent group comparison feature by allowing comparisons inside the Results View page. The new tab allows for quick comparison of altered vs unaltered cases by survival, clinical information, mutation, copy number events and mRNA expression:","group_results640px","Performance enhancement: the Study View's mutation table now loads faster for studies with multiple gene panels. For the genie portal, which has a study with many different gene panels this resulted in a speed-up from ~ 90-120 seconds to 5 seconds.","Read more about the v3.2.2 release here"]},{"i":"january-30-2020","l":"January 30, 2020","p":["Enhancement: Show HGVSg in mutations table and linkout to Genome Nexus:","hgvsg genome nexus","Enhancement: Add a pencil button near gene list in results page which opens interface for quickly modifying the oql of the query:","edit query pencil","See more updates here"]},{"i":"january-29-2020","l":"January 29, 2020","p":["Added data consisting of 197 samples from 2 studies:","Bladder/Urinary Tract Cancer (MSK, 2019) 78 samples","Upper Tract Urothelial Carcinoma (MSK, 2019) 119 samples"]},{"i":"december-19-2019","l":"December 19, 2019","p":["Enhancement: We restored support for submitting large queries from external applications using HTTP POST requests. Accepted parameters are the same as appear in the url of a query submitted from the homepage.","See more updates here"]},{"i":"december-12-2019","l":"December 12, 2019","p":["Enhancement: Several enhancements to the display of gene panels on the Patient View page, by The Hyve, described in more detail here","image","Enhancement: Add Count Bubbles to Oncoprint Toolbar","Screenshot from 2019-12-06 11-36-21","See more updates here"]},{"i":"november-29-2019","l":"November 29, 2019","p":["Enhancement: Support group comparison for custom charts in Study View page","Enhancement: Performance improvement of Co-Expression analysis.","Enhancement: Kaplan-Meier plots now supports custom time range.","See more updates here"]},{"i":"november-22-2019","l":"November 22, 2019","p":["New Feature: Support for Treatment response data in the Oncoprint and Plots tab, including new Waterfall plot type. Read more in The Hyve's blog post","image"]},{"i":"november-15-2019","l":"November 15, 2019","p":["Enhancement: heatmap tracks in OncoPrint now has separate headers and sub-menus. example","image","Enhancement: global settings for query session"]},{"i":"november-7-2019","l":"November 7, 2019","p":["Added data consisting of 212 samples from 3 studies:","Metastatic Melanoma (DFCI, Science 2015) 110 samples","Melanoma (MSKCC, NEJM 2014) 64 samples","Metastatic Melanoma (UCLA, Cell 2016) 38 samples"]},{"i":"october-30-2019","l":"October 30, 2019","p":["Added data consisting of 178 samples from 2 studies:","Intrahepatic Cholangiocarcinoma (Shanghai, Nat Commun 2014) 103 samples","Non-Small Cell Lung Cancer (MSK, Cancer Cell 2018) 75 samples"]},{"i":"october-23-2019","l":"October 23, 2019","p":["Enhancement: Quick example links in Plots tab. example"]},{"i":"october-14-2019","l":"October 14, 2019","p":["New Feature: Fusion Genes table in Study View. example","image"]},{"i":"october-11-2019","l":"October 11, 2019","p":["Enhancement: The Download interface on the homepage has been removed. Enhanced download functionality is now available after querying on the results page.","Home page:","homepage download tab removed","Results page:","results page download tab","Note that as before one can always download the full raw data on the Data Sets page or from Datahub."]},{"i":"october-9-2019","l":"October 9, 2019","p":["Added data consisting of 2725 samples from 4 studies:","Cancer Cell Line Encyclopedia (Broad, 2019) 1739 samples","Chronic Lymphocytic Leukemia (Broad, Nature 2015) 537 samples","Rectal Cancer (MSK,Nature Medicine 2019) 339 samples","Colon Cancer (CPTAC-2 Prospective, Cell 2019) 110 samples","Updated Esophageal Carcinoma (TCGA, Nature 2017) with addition of CNA data for Esophageal Squamous Cell Carcinoma cases 90 samples."]},{"i":"september-18-2019","l":"September 18, 2019","p":["New Feature: The list and order of charts of a study will be automatically saved now as a user preference on the study view page."]},{"i":"september-6-2019","l":"September 6, 2019","p":["Added data consisting of 1216 samples from 3 studies:","Breast Cancer (MSKCC, 2019) 70 samples","Brain Tumor PDXs (Mayo Clinic, 2019) 97 samples","Adenoid Cystic Carcinoma Project (2019) 1049 samples"]},{"i":"august-13-2019","l":"August 13, 2019","p":["Added data consisting of 295 samples from 3 studies:","Pediatric Preclinical Testing Consortium (PPTC, 2019) 261 samples","Non-small cell lung cancer (MSK, Science 2015) 16 samples","Prostate Cancer (MSK, 2019) 18 samples"]},{"i":"july-26-2019","l":"July 26, 2019","p":["Added data consisting of 35 samples from 1 study:","Added Hypoxia data for:","Brain Lower Grade Glioma (TCGA, PanCancer Atlas)","Breast Invasive Carcinoma (TCGA, PanCancer Atlas)","Cervical Squamous Cell Carcinoma (TCGA, PanCancer Atlas)","Clear Cell Renal Cell Carcinoma (DFCI, Science 2019) 35 samples","Colorectal Adenocarcinoma (TCGA, PanCancer Atlas)","Glioblastoma Multiforme (TCGA, PanCancer Atlas)","Head and Neck Squamous Cell Carcinoma (TCGA, PanCancer Atlas)","Kidney Renal Clear Cell Carcinoma (TCGA, PanCancer Atlas)","Kidney Renal Papillary Cell Carcinoma (TCGA, PanCancer Atlas)","Liver Hepatocellular Carcinoma (TCGA, PanCancer Atlas)","Lung Adenocarcinoma (TCGA, PanCancer Atlas)","Lung Squamous Cell Carcinoma (TCGA, PanCancer Atlas)","Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas)","Pancreatic Adenocarcinoma (TCGA, PanCancer Atlas)","Pheochromocytoma and Paraganglioma (TCGA, PanCancer Atlas)","Prostate Adenocarcinoma (TCGA, PanCancer Atlas)","Skin Cutaneous Melanoma (TCGA, PanCancer Atlas)","Thyroid Carcinoma (TCGA, PanCancer Atlas)","Uterine Corpus Endometrial Carcinoma (TCGA, PanCancer Atlas)"]},{"i":"july-24-2019","l":"July 24, 2019","p":["Added data consisting of 151 samples from 1 study:","Myeloproliferative Neoplasms (CIMR, NEJM 2013) 151 samples"]},{"i":"july-13-2019","l":"July 13, 2019","p":["Public Release 6.1 of AACR Project GENIE:","The sixth data set, GENIE 6.0-public, was released in early July 2019. A patch to GENIE 6.0-public, GENIE 6.1-pubic, was subsequently released on July 13, 2019. The combined data set now includes nearly 70,000 de-identified genomic records collected from patients who were treated at each of the consortium's participating institutions, making it among the largest fully public cancer genomic data sets released to date. The combined data set now includes data for nearly 80 major cancer types, including data from nearly 11,000 patients with lung cancer, greater than 9,700 patients with breast cancer, and nearly 7,000 patients with colorectal cancer.","More detailed information can be found in the AACR GENIE Data Guide. In addition to accessing the data via the cBioPortal, users can download the data directly from Sage Bionetworks. Users will need to create an account for either site and agree to the terms of access.","For frequently asked questions, visit the AACR FAQ page."]},{"i":"july-2-2019","l":"July 2, 2019","p":["Added data consistng of 785 samples from 4 studies:","Non-Small Cell Lung Cancer (TRACERx, NEJM 2017) 327 samples","Acute myeloid leukemia or myelodysplastic syndromes (WashU, 2016) 136 samples","Basal Cell Carcinoma (UNIGE, Nat Genet 2016) 293 samples","Colon Adenocarcinoma (CaseCCC, PNAS 2015) 29 samples"]},{"i":"june-19-2019","l":"June 19, 2019","p":["New Feature: Show Genome Aggregation Database (gnomAD) population frequencies in the mutations table - see example:","gnomad feature news"]},{"i":"june-12-2019","l":"June 12, 2019","p":["Added data of 1350 samples from 3 studies:","Pheochromocytoma and Paraganglioma (TCGA, Cell 2017) 178 samples","Metastatic Solid Cancers (UMich, Nature 2017) 500 samples","Acute Myeloid Leukemia (OHSU, Nature 2018) 672 samples","Added survival data for TCGA PanCan Atlas Cohorts (>10,000 samples across 33 tumor types).","Added hypoxia data for Bladder Urothelial Carcinoma (TCGA, PanCancer Atlas)"]},{"i":"june-7-2019","l":"June 7, 2019","p":["New Group Comparison Feature: Compare clinical and genomic features of user-defined groups of samples/patients. View Tutorial","group-comparison"]},{"i":"may-8-2019","l":"May 8, 2019","p":["New Feature: Show Post Translational Modification (PTM) information from dbPTM on the Mutation Mapper- see example:","ptm feature_news"]},{"i":"april-26-2019","l":"April 26, 2019","p":["Added data of 568 samples from 4 studies:","Adenoid Cystic Carcinoma (JHU, Cancer Prev Res 2016) 25 samples","Histiocytosis Cobimetinib (MSK, Nature 2019) 52 samples","Upper Tract Urothelial Carcinoma (Cornell/Baylor/MDACC, Nat Comm 2019) 47 samples","Metastatic Prostate Adenocarcinoma (SU2C/PCF Dream Team, PNAS 2019) 444 samples"]},{"i":"march-29-2019","l":"March 29, 2019","p":["New Feature: Use the new quick search tab on the homepage to more easily navigate to a study, gene or patient:","quick_search_news"]},{"i":"march-15-2019","l":"March 15, 2019","p":["Added data of 338 samples from 4 studies:","Adenoid Cystic Carcinoma (MGH, Nat Gen 2016) 10 samples","Gallbladder Cancer (MSK, Cancer 2018) 103 samples","The Metastatic Prostate Cancer Project (Provisional, December 2018) 19 samples","Adult Soft Tissue Sarcomas (TCGA, Cell 2017) 206 samples"]},{"i":"february-22-2019","l":"February 22, 2019","p":["Enhancement: Exon number and HGVSc annotations are available in optional columns in the Mutations tab on the Results page and in the Patient View.","New feature: option to a show regression line in the scatter plot in the Plots tab on the Results page","image"]},{"i":"february-19-2019","l":"February 19, 2019","p":["New feature: Copy-Number Segments tab on the Study View page using igv.js v2- see example","Improved Copy-Number Segments tab on the Results page","New feature: OncoKB and Cancer Hotspots tracks in the Mutations tab on the Results page","image"]},{"i":"january-24-2019","l":"January 24, 2019","p":["Added data of 2328 samples from 8 studies:","Uveal Melanoma (QIMR, Oncotarget 2016) 28 samples","Squamous Cell Carcinoma of the Vulva (CUK, Exp Mol Med 2018) 15 samples","TMB and Immunotherapy (MSKCC, Nat Genet 2019) 1661 samples","Glioma (MSK, 2018) 91 samples","Urothelial Carcinoma (Cornell/Trento, Nat Gen 2016) 72 samples","Hepatocellular Carcinoma (MSK, Clin Cancer Res 2018) 127 samples","MSK Thoracic PDX (MSK, Provisional) 139 samples","Cholangiocarcinoma (MSK, Clin Cancer Res 2018) 195 samples","Updated data for The Metastatic Breast Cancer Project (Provisional, October 2018) 237 samples"]},{"i":"january-10-2019","l":"January 10, 2019","p":["cBioPortal now supports queries for driver mutations, fusions and copy number alterations as well as germline/somatic mutations using Onco Query Language (OQL)-- see example","A new tutorial explores OQL and provides examples of how OQL can be a powerful tool to refine queries."]},{"i":"december-17-2018","l":"December 17, 2018","p":["The 10th phase of cBioPortal architectural upgrade is now complete: the Study View has been moved to the new architecture with numerous improvements. This marks the completion of the cBioPortal architectural refactoring! \uD83C\uDF89\uD83C\uDF89\uD83C\uDF89","image"]},{"i":"october-29-2018","l":"October 29, 2018","p":["The ninth phase of the cBioPortal architectural upgrade is now complete: the results page is now a single-page application with better performance.","Supported plotting mutations by type in Plots tab","image"]},{"i":"october-19-2018","l":"October 19, 2018","p":["Support selection of transcript of interest in the MutationMapper tool via Genome Nexus.","mutation_mapper_dropdown"]},{"i":"october-17-2018","l":"October 17, 2018","p":["Added data of 3578 samples from 8 studies:","Rhabdoid Cancer (BCGSC, Cancer Cell 2016) 40 samples","Diffuse Large B-Cell Lymphoma (Duke, Cell 2017) 1001 samples","Diffuse Large B cell Lymphoma (DFCI, Nat Med 2018) 135 samples","Breast Fibroepithelial Tumors (Duke-NUS, Nat Genet 2015) 22 samples","Uterine Clear Cell Carcinoma (NIH, Cancer 2017) 16 samples","Endometrial Cancer (MSK, 2018) 197 samples","Breast Cancer (MSK, Cancer Cell 2018) 1918 samples","MSS Mixed Solid Tumors (Van Allen, 2018) 249 samples","Updated data for The Angiosarcoma Project (Provisional, September 2018) 48 samples"]},{"i":"august-20-2018","l":"August 20, 2018","p":["Now you can log in on the public cBioPortal with your Google account and save your virtual studies for quick analysis.","image"]},{"i":"august-7-2018","l":"August 7, 2018","p":["The eighth phase of the cBioPortal architectural upgrade is now complete: The Plots, Expression, Network, and Bookmarks tabs, and therefore all analysis tabs in the results page, have been moved to the new architecture.","Updated the MutationMapper tool, now connecting to Genome Nexus for annotating mutations on the fly.","Total Mutations and Fraction Genome Altered are now available in Plots tab for visualization and analysis.","Enhanced clinical attribute selector for OncoPrint, now showing sample counts per attribute.","image"]},{"i":"july-27-2018","l":"July 27, 2018","p":["Added data of 2787 samples from 10 studies:","Mixed Tumors (PIP-Seq 2017) 103 samples","Nonmuscle Invasive Bladder Cancer (MSK Eur Urol 2017) 105 samples","Pediatric Neuroblastoma (TARGET, 2018) 1089 samples","Pediatric Pan-Cancer (DKFZ - German Cancer Consortium, 2017) 961 samples","Skin Cutaneous Melanoma (Broad, Cancer Discov 2014) 78 samples","Cutaneous Squamous Cell Carcinoma (MD Anderson, Clin Cancer Res 2014) 39 samples","Diffuse Large B-cell Lymphoma (BCGSC, Blood 2013) 53 samples","Non-Hodgkin Lymphoma (BCGSC, Nature 2011) 14 samples","Chronic lymphocytic leukemia (ICGA, Nat 2011) 105 samples","Neuroblastoma (Broad Institute 2013) 240 samples"]},{"i":"june-20-2018","l":"June 20, 2018","p":["The seventh phase of the cBioPortal architectural upgrade is now complete: The Enrichments and Co-Expression tabs have been moved to the new architecture.","Supported merged gene tracks in OncoPrint and Onco Query Language-- see example","image"]},{"i":"may-10-2018","l":"May 10, 2018","p":["Enhanced OncoPrint to show germline mutations -- see example","image"]},{"i":"april-17-2018","l":"April 17, 2018","p":["Acute Lymphoblastic Leukemia (St Jude, Nat Genet 2016) 73 samples","Added data of 3416 samples from 10 published studies:","Added data of 3732 samples from 4 TARGET studies:","Bladder Cancer (TCGA, Cell 2017) 413 samples","Colorectal Cancer (MSK, Cancer Cell 2018) 1134 samples","Metastatic Esophagogastric Cancer (MSK,Cancer Discovery 2017) 341 samples","Non-Small Cell Lung Cancer (MSK, JCO 2018) 240 samples","Pediatric Acute Lymphoid Leukemia - Phase II (TARGET, 2018) 1978 samples","Pediatric Acute Myeloid Leukemia (TARGET, 2018) 1025 samples","Pediatric Rhabdoid Tumor (TARGET, 2018) 72 samples","Pediatric Wilms' Tumor (TARGET, 2018) 657 samples","Prostate Adenocarcinoma (EurUrol, 2017) 65 samples","Prostate Adenocarcinoma (MSKCC/DFCI, Nature Genetics 2018) 1013 samples","Small-Cell Lung Cancer (Multi-Institute 2017) 20 samples","The Angiosarcoma Project (Provisional, February 2018) 14 samples","Updated Segment data and Allele Frequencies for The Metastatic Breast Cancer Project (Provisional, October 2017) 103 samples"]},{"i":"april-5-2018","l":"April 5, 2018","p":["Acute Myeloid Leukemia (TCGA, PanCancer Atlas)","Added data from the TCGA PanCanAtlas project with >10,000 samples from 33 tumor types:","Adrenocortical Carcinoma (TCGA, PanCancer Atlas)","Bladder Urothelial Carcinoma (TCGA, PanCancer Atlas)","Brain Lower Grade Glioma (TCGA, PanCancer Atlas)","Breast Invasive Carcinoma (TCGA, PanCancer Atlas)","Cervical Squamous Cell Carcinoma (TCGA, PanCancer Atlas)","Cholangiocarcinoma (TCGA, PanCancer Atlas)","Colon Adenocarcinoma (TCGA, PanCancer Atlas)","Diffuse Large B-Cell Lymphoma (TCGA, PanCancer Atlas)","Esophageal Adenocarcinoma (TCGA, PanCancer Atlas)","Glioblastoma Multiforme (TCGA, PanCancer Atlas)","Head and Neck Squamous Cell Carcinoma (TCGA, PanCancer Atlas)","Kidney Chromophobe (TCGA, PanCancer Atlas)","Kidney Renal Clear Cell Carcinoma (TCGA, PanCancer Atlas)","Kidney Renal Papillary Cell Carcinoma (TCGA, PanCancer Atlas)","Liver Hepatocellular Carcinoma (TCGA, PanCancer Atlas)","Lung Adenocarcinoma (TCGA, PanCancer Atlas)","Lung Squamous Cell Carcinoma (TCGA, PanCancer Atlas)","Mesothelioma (TCGA, PanCancer Atlas)","Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas)","Pancreatic Adenocarcinoma (TCGA, PanCancer Atlas)","Pheochromocytoma and Paraganglioma (TCGA, PanCancer Atlas)","Prostate Adenocarcinoma (TCGA, PanCancer Atlas)","Rectum Adenocarcinoma (TCGA, PanCancer Atlas)","Sarcoma (TCGA, PanCancer Atlas)","Skin Cutaneous Melanoma (TCGA, PanCancer Atlas)","Stomach Adenocarcinoma (TCGA, PanCancer Atlas)","Testicular Germ Cell Tumors (TCGA, PanCancer Atlas)","Thymoma (TCGA, PanCancer Atlas)","Thyroid Carcinoma (TCGA, PanCancer Atlas)","Uterine Carcinosarcoma (TCGA, PanCancer Atlas)","Uterine Corpus Endometrial Carcinoma (TCGA, PanCancer Atlas)","Uveal Melanoma (TCGA, PanCancer Atlas)"]},{"i":"march-20-2018","l":"March 20, 2018","p":["The sixth phase of the cBioPortal architectural upgrade is now complete: The Download tab has been moved to the new architecture.","Data can now be downloaded in tabular format from OncoPrint.","Added an option to download an SVG file on the Cancer Type Summary tab."]},{"i":"january-15-2018","l":"January 15, 2018","p":["The fifth phase of the cBioPortal architectural upgrade is now complete: The OncoPrint and Survival tabs have been moved to the new architecture."]},{"i":"november-20-2017","l":"November 20, 2017","p":["You can now combine multiple studies and view them on the study summary page. Example: liver cancer studies","You can now bookmark or share your selected samples as virtual studies with the share icon on the study summary page. Example: a virtual study of breast tumors","Cross-study query reimplemented: Now you can view an OncoPrint of multiple studies. Example: querying NSCLC tumors from 5 studies","image"]},{"i":"october-17-2017","l":"October 17, 2017","p":["The fourth phase of the cBioPortal architectural upgrade is now complete: The Mutual Exclusivity and Cancer Type Summary tabs have been moved to the new architecture.","Updated protein structure alignment data in Mutations tab are now retrieved from Genome Nexus via the G2S web service."]},{"i":"october-2-2017","l":"October 2, 2017","p":["Added data of 1646 samples from 7 published studies:","NGS in Anaplastic Oligodendroglioma and Anaplastic Oligoastrocytomas tumors (MSK, Neuro Oncol 2017) 22 samples","MSK-IMPACT Clinical Sequencing Cohort for Non-Small Cell Cancer (MSK, Cancer Discovery 2017) 915 samples","Paired-exome sequencing of acral melanoma (TGEN, Genome Res 2017) 38 samples","MSK-IMPACT Clinical Sequencing Cohort in Prostate Cancer (MSK, JCO Precision Oncology 2017) 504 samples","Whole-exome sequences (WES) of pretreatment melanoma tumors (UCLA, Cell 2016) 39 samples","Next generation sequencing (NGS) of pre-treatment metastatic melanoma samples (MSK, JCO Precision Oncology 2017) 66 samples","Targeted gene sequencing in 62 high-grade primary Unclassified Renal Cell Carcinoma (MSK, Nature 2016) 62 samples","Updated data for MSK-IMPACT Clinical Sequencing Cohort (MSK, Nat Med 2017) with overall survival data."]},{"i":"august-3-2017","l":"August 3, 2017","p":["The third phase of the cBioPortal architectural upgrade is now complete: The Mutations tab now has a fresh look and faster performance -- see example","image","Variant interpretations from the CIViC database are now integrated into the annotation columns on the Mutations tab and in the patient view pages","New summary graph for all cancer studies and samples on the front page"]},{"i":"june-26-2017","l":"June 26, 2017","p":["The second phase of the cBioPortal architectural upgrade is now complete: The query interface now has a fresh look and faster performance.","image"]},{"i":"may-12-2017","l":"May 12, 2017","p":["Added data of 12,211 samples from 11 published studies:","MSK-IMPACT Clinical Sequencing Cohort (MSK, Nat Med 2017) 10,945 samples","Whole-genome sequencing of pilocytic astrocytomasatic (DKFZ, Nat Genetics, 2013) 96 samples","Hepatocellular Carcinomas (INSERM, Nat Genet 2015) 243 samples","Cystic Tumor of the Pancreas (Johns Hopkins, PNAS 2011) 32 samples","Whole-Genome Sequencing of Pancreatic Neuroendocrine Tumors (ARC- Net, Nature, 2017) 98 samples","Medulloblastoma (Sickkids, Nature 2016) 46 samples","Genetic Characterization of NSCLC young adult patients (University of Turin, Lung Cancer 2016) 41 samples","Genomic Profile of Patients with Advanced Germ Cell Tumors (MSK, JCO 2016). 180 samples","Ampullary Carcinoma (Baylor, Cell Reports 2016) 160 samples","Mutational profiles of metastatic breast cancer (INSERM, 2016) 216 samples","Prostate Adenocarcinoma (Fred Hutchinson CRC, Nat Med 2016) 154 samples"]},{"i":"may-5-2017","l":"May 5, 2017","p":["First phase of cBioPortal architectural upgrade complete: Patient view now has fresh look and faster performance. example"]},{"i":"march-28-2017","l":"March 28, 2017","p":["New features:","Per-sample mutation spectra are now available in OncoPrints -- see example","image","mRNA heat map clustering is now supported in OncoPrints","MDACC Next-Generation Clustered Heat Maps are now available in the patient view","cBioPortal web site style change"]},{"i":"feburary-2-2017","l":"Feburary 2, 2017","p":["New features:","3D hotspot mutation annotations are now available from 3dhotspots.org","New data:","CPTAC proteomics data have been integrated for TCGA breast, ovarian, and colorectal provisional studies"]},{"i":"december-23-2016","l":"December 23, 2016","p":["New features:","Heat map visualization of gene expression data in the OncoPrint","OncoPrint Heatmap","Heat map visualization of gene expression data in the Study View page connecting to MDACC's TCGA Next-Generation Clustered Heat Map Compendium"]},{"i":"october-7-2016","l":"October 7, 2016","p":["New features:","All data sets can now be downloaded as flat files from the new Data Hub","Annotation of putative driver missense mutations in OncoPrints, based on OncoKB, mutation hotspots, and recurrence in cBioPortal and COSMIC","OncoPrint-OncoKB","Copy number segments visualization directly in the browser in a new CN Segments tab via IGV.js","image","Improvements:","Improved cancer study view page (bug fixes and increased performance)"]},{"i":"july-24-2016","l":"July 24, 2016","p":["Added data of 4,375 samples from 21 published studies:","Adenoid Cystic Carcinoma (FMI, Am J Surg Pathl. 2014) 28 samples","Adenoid Cystic Carcinoma (MDA, Clin Cancer Res 2015) 102 samples","Adenoid Cystic Carcinoma (Sanger/MDA, JCI 2013) 24 samples","Adenoid Cystic Carcinoma of the Breast (MSKCC, J Pathol. 2015) 12 samples","Bladder Cancer, Plasmacytoid Variant (MSKCC, Nat Genet 2016) 34 samples","Breast Cancer (METABRIC, Nat Commun 2016) 1980 samples","Chronic Lymphocytic Leukemia (Broad, Cell 2013) 160 samples","Chronic Lymphocytic Leukemia (IUOPA, Nature 2015) 506 samples","Colorectal Adenocarcinoma (DFCI, Cell Reports 2016) 619 samples","Cutaneous T Cell Lymphoma (Columbia U, Nat Genet 2015) 42 samples","Diffuse Large B-Cell Lymphoma (Broad, PNAS 2012) 58 samples","Hepatocellular Adenoma (Inserm, Cancer Cell 2014) 46 samples","Hypodiploid Acute Lymphoid Leukemia (St Jude, Nat Genet 2013) 44 samples","Insulinoma (Shanghai, Nat Commun 2013) 10 samples","Malignant Pleural Mesothelioma (NYU, Cancer Res 2015) 22 samples","Mantle Cell Lymphoma (IDIBIPS, PNAS 2013) 29 samples","Myelodysplasia (Tokyo, Nature 2011) 29 samples","Neuroblastoma (Broad, Nat Genet 2013) 56 samples","New TCGA study:","OncoTree codes assigned per sample","Oral Squamous Cell Carcinoma (MD Anderson, Cancer Discov 2013) 40 samples","Pan-Lung Cancer (TCGA, Nat Genet 2016) 1144 samples","Pancreatic Adenocarcinoma (QCMG, Nature 2016) 383 samples","Recurrent and Metastatic Head & Neck Cancer (JAMA Oncology, 2016) 151 samples","RPPA data updated with the latest data from MD Anderson","Updated TCGA provisional studies","updated to the Firehose run of January 28, 2016"]},{"i":"june-6-2016","l":"June 6, 2016","p":["New features:","Annotation of mutation effect and drug sensitivity on the Mutations tab and the patient view pages (via OncoKB) oncokb-screenshot","Improvements:","Improved OncoPrint visualization using WebGL: faster, more zooming flexibility, visualization of recurrent variants","Improved Network tab with SBGN view for a single interaction","Performance improvement of tables in the study view page","Mutation type summary on the Mutations tab"]},{"i":"march-31-2016","l":"March 31, 2016","p":["New features:","Visualization of \"Enrichments Analysis\" results via volcano plots","Improved performance of the cross cancer expression view by switching to Plot.ly graphs","Improvements to the \"Clinical Data\" tab on the study view page","More customization options for the cross-cancer histograms","Performance improvements in the study view and query result tabs","Added data of 1235 samples from 3 published studies:","Merged Cohort of LGG and GBM (TCGA, 2016)","Lung Adenocarcinoma (MSKCC, 2015)","Poorly-Differentiated and Anaplastic Thyroid Cancers (MSKCC, JCI 2016)"]},{"i":"january-12-2016","l":"January 12, 2016","p":["Acinar Cell Carcinoma of the Pancreas (Johns Hopkins, J Pathol 2014)","Added data of 650 samples from 10 published studies:","All mutation data mapped to UniProt canonical isoforms","All TCGA data updated to the latest Firehose run of August 21, 2015","Bladder Urothelial Carcinoma (Dana Farber & MSKCC, Cancer Discovery 2014)","Cholangiocarcinoma (TCGA, Provisional)","Clear Cell Renal Cell Carcinoma (U Tokyo, Nat Genet 2013)","Desmoplastic Melanoma (Broad Institute, Nat Genet 2015)","Esophageal Squamous Cell Carcinoma (UCLA, Nat Genet 2014)","Gastric Adenocarcinoma (TMUCIH, PNAS 2015)","Low-Grade Gliomas (UCSF, Science 2014)","Mesothelioma (TCGA, Provisional)","Multiregion Sequencing of Clear Cell Renal Cell Carcinoma (IRC, Nat Genet 2014)","Neuroblastoma (AMC Amsterdam, Nature 2012)","New features:","New TCGA studies:","Primary Central Nervous System Lymphoma (Mayo Clinic, Clin Cancer Res 2015)","Testicular Germ Cell Cancer (TCGA, Provisional)","Thymoma (TCGA, Provisional)","Visualization of multiple samples in a patient","Visualization of timeline data of a patient ( example) timeline-example"]},{"i":"december-23-2015","l":"December 23, 2015","p":["New features:","Visualization of RNA-seq expression levels across TCGA studies (cross-cancer queries) cross cancer expression","Selection of genes in the study view to initiate queries query gene in study view","Improvement:","3-D structures in the \"Mutations\" tab are now rendered by 3Dmol.js (previously JSmol)","Improved performance by code optimization and compressing large data by gzip"]},{"i":"december-1-2015","l":"December 1, 2015","p":["New feature: Annotated statistically recurrent hotspots, via new algorithm by Chang et al. 2015 Annotate recurrent hotspots"]},{"i":"november-9-2015","l":"November 9, 2015","p":["New features:","Links to MyCancerGenome.org for mutations Link to MyCancerGenome.org","Improved display of selection samples on the study view page","Improvements:","\"Enrichments\" analysis is now run across all genes","The \"Network\" tab is now using Cytoscape.js (Adobe Flash is no longer required)"]},{"i":"october-6-2015","l":"October 6, 2015","p":["Added data of 763 samples from 12 published studies:","Breast Invasive Carcinoma (TCGA, Cell 2015)","Cutaneous squamous cell carcinoma (DFCI, Clin Cancer Res 2015)","Ewing Sarcoma (Institut Cuire, Cancer Discov 2014)","Gallbladder Carcinoma (Shanghai, Nat Genet 2014)","Infant MLL-Rearranged Acute Lymphoblastic Leukemia (St Jude, Nat Genet 2015)","Microdissected Pancreatic Cancer Whole Exome Sequencing (UTSW, Nat Commun 2015)","New TCGA data:","Pancreatic Neuroendocrine Tumors (JHU, Science 2011)","Pediatric Ewing Sarcoma (DFCI, Cancer Discov 2014)","Prostate Adenocarcinoma (TCGA, in press)","Renal Non-Clear Cell Carcinoma (Genentech, Nat Genet 2014)","Rhabdomyosarcoma (NIH, Cancer Discov 2014)","Small Cell Lung Cancer (U Cologne, Nature 2015)","Thymic epithelial tumors (NCI, Nat Genet 2014)","Uterine Carcinosarcoma (JHU, Nat Commun 2014)","Uveal Melanoma (TCGA, Provisional)"]},{"i":"august-21-2015","l":"August 21, 2015","p":["All TCGA data updated to the Firehose run of April 16, 2015.","New feature: Enrichments Analysis finds alterations that are enriched in either altered or unaltered samples.","Improvement: improved OncoPrint with better performance."]},{"i":"june-3-2015","l":"June 3, 2015","p":["Improvements:","Allowed downloading data in each chart/table in study summary page.","Added log-rank test p-values to the survival plots in study summary page.","Improved visualization of patient clinical data in patient-centric view.","Added option to merge multiple samples for the same patient in OncoPrint."]},{"i":"april-28-2015","l":"April 28, 2015","p":["New features:","Redesigned query interface to allow selecting multiple cancer studies","Redesigned Plots tab"]},{"i":"january-20-2015","l":"January 20, 2015","p":["All TCGA data updated to the Firehose run of October 17, 2014","COSMIC data updated to V71","New features:","Query page: better search functions to find cancer studies","OncoPrints now support color coding of different mutation types","OncoPrints now support multiple clinical annotation tracks","OncoPrinter tool now supports mRNA expression changes Oncoprint with multiple clinical tracks"]},{"i":"january-6-2015","l":"January 6, 2015","p":["New feature: You can now view frequencies of mutations and copy-number alterations in the study view. These tables are updated dynamically when selecting subsets of samples. Alterations in heavily copy-number altered endometrial cancer cases"]},{"i":"december-9-2014","l":"December 9, 2014","p":["New TCGA data:","Added complete and up-to-date clinical data for all TCGA provisional studies","All TCGA data updated to the Firehose run of July 15, 2014","New TCGA provisional studies: Esophageal cancer, Pheochromocytoma and Paraganglioma (PCPG)","New published TCGA studies: Thyroid Cancer and Kidney Chromophobe","Added data of 172 samples from 4 published studies:","Cholangiocarcinoma (National University of Singapore, Nature Genetics 2012)","Cholangiocarcinoma (National Cancer Centre of Singapore, Nature Genetics 2013)","Intrahepatic Cholangiocarcinoma (Johns Hopkins University, Nature Genetics 2013)","Bladder Cancer (MSKCC, Eur Urol 2014)","New features:","Redesigned Mutual Exclusivity tab","Added correlation scores for scatter plots on the Plots tab","Download links to GenomeSpace"]},{"i":"october-24-2014","l":"October 24, 2014","p":["Added data of 885 samples from 11 published studies:","Colorectal Adenocarcinoma Triplets (MSKCC, Genome Biology 2014)","Esophageal Squamous Cell Carcinoma (ICGC, Nature 2014)","Malignant Peripheral Nerve Sheath Tumor (MSKCC, Nature Genetics 2014)","Melanoma (Broad/Dana Farber, Nature 2012)","Nasopharyngeal Carcinoma (National University Singapore, Nature Genetics 2014)","Prostate Adenocarcinoma CNA study (MSKCC, PNAS 2014)","Prostate Adenocarcinoma Organoids (MSKCC, Cell 2014)","Stomach Adenocarcinoma (TCGA, Nature 2014)","Stomach Adenocarcinoma (Pfizer and University of Hong Kong, Nature Genetics 2014)","Stomach Adenocarcinoma (University of Hong Kong, Nature Genetics 2011)","Stomach Adenocarcinoma (University of Tokyo, Nature Genetics 2014)"]},{"i":"august-8-2014","l":"August 8, 2014","p":["Released two new tools","Oncoprinter lets you create Oncoprints from your own, custom data","MutationMapper draws mutation diagrams (lollipop plots) from your custom data"]},{"i":"may-21-2014","l":"May 21, 2014","p":["All TCGA data updated to the Firehose run of April 16, 2014"]},{"i":"may-12-2014","l":"May 12, 2014","p":["Improved study summary page including survival analysis based on clinical attributes e.g. TCGA Endometrial Cancer cohort Study view"]},{"i":"march-27-2014","l":"March 27, 2014","p":["New features:","Visualizing of mutations mapped on 3D structures (individual or multiple mutations, directly in the browser)","Gene expression correlation analysis (find all genes with expression correlation to your query genes)","The Patient-Centric View now displays mutation frequencies across all cohorts in cBioPortal for each mutation","The Mutation Details Tab and the Patient-Centric View now display the copy-number status of each mutation 3D viewer & Co-expression"]},{"i":"march-18-2014","l":"March 18, 2014","p":["Added mutation data of 898 samples from 11 published studies:","Added two new provisional TCGA studies:","Adrenocortical Carcinoma","All TCGA data updated to the Firehose run of January 15, 2014","Hepatocellular Carcinoma (AMC, Hepatology in press)","Hepatocellular Carcinoma (RIKEN, Nature Genetics 2012)","Medulloblastoma (Broad, Nature 2012)","Medulloblastoma (ICGC, Nature 2012)","Medulloblastoma (PCGP, Nature 2012)","Multiple Myeloma (Broad, Cancer Cell 2014)","NCI-60 Cell Lines (NCI, Cancer Res. 2012)","Pancreatic Adenocarcinoma (ICGC, Nature 2012)","Small Cell Carcinoma of the Ovary (MSKCC, Nature Genetics in press)","Small Cell Lung Cancer (CLCGP, Nature Genetics 2012)","Small Cell Lung Cancer (Johns Hopkins, Nature Genetics 2012)","Updated to the latest COSMIC data (v68)","Uterine Carcinosarcoma"]},{"i":"december-9-2013","l":"December 9, 2013","p":["Added mutation data of 99 bladder cancer samples (BGI, Nature Genetics 2013)"]},{"i":"december-6-2013","l":"December 6, 2013","p":["Data sets matching four recently submitted or published TCGA studies are now available","Glioblastoma (Cell 2013)","Bladder carcinoma (Nature, in press)","Head & neck squamous cell carcinoma (submitted)","Lung adenocarcinoma (submitted)"]},{"i":"november-8-2013","l":"November 8, 2013","p":["All TCGA data updated to the Firehose run of September 23, 2013.","Updated to the latest COSMIC data (v67).","Added mutation data of 792 samples from 9 published cancer studies:","Esophageal Adenocarcinoma (Broad, Nature Genetics 2013)","Head and Neck Squamous Cell Carcinoma (Broad, Science 2011)","Head and Neck Squamous Cell Carcinoma (Johns Hopkins, Science 2011)","Kidney Renal Clear Cell Carcinoma (BGI, Nature Genetics 2012)","Prostate Adenocarcinoma, Metastatic (Michigan, Nature 2012)","Prostate Adenocarcinoma (Broad/Cornell, Nature Genetics 2012)","Prostate Adenocarcinoma (Broad/Cornell, Cell 2013)","Skin Cutaneous Melanoma (Yale, Nature Genetics 2012)","Skin Cutaneous Melanoma (Broad, Cell 2012)"]},{"i":"october-21-2013","l":"October 21, 2013","p":["Improved interface for survival plots, including information on individual samples via mouse-over","New fusion glyph in OncoPrints FGFR3 fusions in head and neck carcinoma","Improved cross-cancer query: new alteration frequency histogram (example below - query gene: CDKN2A) and mutation diagram Cross Cancer Query"]},{"i":"september-9-2013","l":"September 9, 2013","p":["Updated COSMIC data (v66 Release)","Improved / interactive visualization on the \"Protein changes\" tab","Enhanced mutation diagrams: color-coding by mutation time and syncing with table filters","Addition of DNA cytoband information in the patient view of copy-number changes","OncoPrints now allow the display of an optional track with clinical annotation (Endometrial cancer example below) Oncoprint with clinical track"]},{"i":"july-25-2013","l":"July 25, 2013","p":["Multi-gene correlation plots.","Variant allele frequency distribution plots for individual tumor samples.","Tissue images for TCGA samples in the patient view, via Digital Slide Archive. Example."]},{"i":"july-16-2013","l":"July 16, 2013","p":["All TCGA data updated to the May Firehose run (May 23, 2013).","TCGA Pancreatic Cancer study (provisional) added."]},{"i":"july-4-2013","l":"July 4, 2013","p":["Improved rendering of mutation diagrams, including ability to download in PDF format.","Improved home page: Searchable cancer study & gene set selectors, data sets selector."]},{"i":"june-17-2013","l":"June 17, 2013","p":["Improved interface for correlation plots, including information on individual samples via mouse-over.","Gene Details from Biogene are now available in the Network view.","Added mutation and copy number data from a new adenoid cystic carcinoma study: Ho et al., Nature Genetics 2013.","Added mutation data from 6 cancer studies.","Breast Invasive Carcinoma (Shah et al., Nature 2012)","Breast Invasive Carcinoma (Banerji et al., Nature 2012)","Breast Invasive Carcinoma (Stephens et al., Nature 2012)","Lung Adenocarcinoma (Imielinksi et al., Cell 2012)","Lung Adenocarcinoma (Ding et al., Nature 2008)","Colorectal Cancer (Seshagiri et al., Nature 2012)"]},{"i":"june-4-2013","l":"June 4, 2013","p":["All TCGA data updated to the April Firehose run (April 21, 2012)."]},{"i":"may-14-2013","l":"May 14, 2013","p":["Added a published TCGA study: Acute Myeloid Leukemia (TCGA, NEJM 2013)."]},{"i":"april-28-2013","l":"April 28, 2013","p":["All TCGA data updated to the March Firehose run (March 26, 2012).","mRNA percentiles for altered genes shown in patient view."]},{"i":"april-2-2013","l":"April 2, 2013","p":["All TCGA data updated to the February Firehose run (February 22, 2012)."]},{"i":"march-28-2013","l":"March 28, 2013","p":["All TCGA data updated to the January Firehose run (January 16, 2012).","Data from a new bladder cancer study from MSKCC has been added (97 samples, Iyer et al., JCO in press)."]},{"i":"february-16-2013","l":"February 16, 2013","p":["The cBio Portal now contains mutation data from all provisional TCGA projects. Please adhere to the TCGA publication guidelines when using these and any TCGA data in your publications.","All data updated to the October Firehose run (October 24, 2012).","Sequencing read counts and frequencies are now shown in the Mutation Details table when available.","Improved OncoPrints, resulting in performance improvements."]},{"i":"november-21-2012","l":"November 21, 2012","p":["Major new feature: Users can now visualize genomic alterations and clinical data of individual tumors, including:","Summary of mutations and copy-number alterations of interest","Clinical trial information","TCGA Pathology Reports","New cancer summary view(Example Endometrial Cancer)","Updated drug data from KEGG DRUG and NCI Cancer Drugs (aggregated by PiHelper)"]},{"i":"october-22-2012","l":"October 22, 2012","p":["All data updated to the Broad Firehose run from July 25, 2012.","COSMIC data added to Mutation Details (via Oncotator).","All predicted functional impact scores are updated to Mutation Assessor 2.0.","Users can now base queries on genes in recurrent regions of copy-number alteration (from GISTIC via Firehose).","The Onco Query Language (OQL) now supports queries for specific mutations or mutation types.","Data sets added that match the data of all TCGA publications (GBM, ovarian, colorectal, and lung squamous)."]},{"i":"july-18-2012","l":"July 18, 2012","p":["Mutation data for the TCGA lung squamous cell carcinoma and breast cancer projects (manuscripts in press at Nature).","All data updated to the latest Broad Firehose run(May 25, 2012).","Drug information added to the network view (via Drugbank).","Improved cross-cancer queries: Option to select data types, export of summary graphs.","Users can now base queries on frequently mutated genes (from MutSig via Firehose)."]},{"i":"may-16-2012","l":"May 16, 2012","p":["All data updated to the latest Broad Firehose run(March 21, 2012).","Extended cross-cancer functionality, enabling users to query across all cancer studies in our database.","New \"build a case\" functionality, enabling users to generate custom case sets, based on one or more clinical attributes.","New OncoPrint features, including more compact OncoPrints, and support for RPPA visualization."]},{"i":"february-27-2012","l":"February 27, 2012","p":["All data updated to the latest Broad Firehose run(January 24, 2012).","Validated mutation data for colorectal cancer.","New feature: Mutation Diagrams that show mutations in the context of protein domains. TP53 Mutations in Ovarian Cancer"]},{"i":"january-30-2012","l":"January 30, 2012","p":["Updated data for several TCGA cancer studies.","Some small bug-fixes."]},{"i":"december-22-2011","l":"December 22, 2011","p":["Fourteen new TCGA cancer studies: This includes complete data for TCGA Colorectal Carcinoma and provisional data for thirteen other cancer types in the TCGA production pipeline. Please note that data from these thirteen new cancer types are provisional, not final and do not yet include mutation data. As per NCI guidelines, preliminary mutation data cannot be redistributed until they have been validated. TCGA","Four new data types:","Reverse-phase protein array (RPPA) data.","microRNA expression and copy-number (including support for multiple loci)","RNA-Seq based expression data.","log2 copy-number data.","Updated TCGA GBM copy-number, expression, and methylation data.","New gene symbol validation service. You can now use gene aliases and/or Entrez Gene IDs within your gene sets.","Links to IGV for visualization of DNA copy-number changes.","Background information from the Sanger Cancer Gene Census.","Two new Tutorials to get you quickly started in using the portal."]},{"i":"november-14-2011","l":"November 14, 2011","p":["New and improved mutation details, with sorting and filtering capabilities.","In collaboration with Bilkent University, we have added a new Network tab to our results pages. The network tab enables users to visualize, analyze and filter cancer genomic data in the context of pathways and interaction networks derived from Pathway Commons. GBM Network"]},{"i":"september-3-2011","l":"September 3, 2011","p":["You can now query across different cancer studies (feature available directly from the home page).","Our MATLAB CGDS Cancer Genomics Toolbox is now available. The toolbox enables you to download data from the cBio Portal, and import it directly into MATLAB.","The code for the cBio Portal has now been fully open sourced, and made available at Google Code. If you would like to join our open source efforts and make the portal even better, drop us an email."]},{"i":"march-2-2011","l":"March 2, 2011","p":["New plotting features and other improvements:","Correlation plots that show the relationship between different data types for individual genes.","Survival analysis - assess survival differences between altered and non-altered patient sets.","Updated R Package with support for correlation plots and general improvements for retrieving and accessing data in R data frames.","The Web Interface now supports basic clinical data, e.g. survival data.","Networks for pathway analysis are now available for download. Survival Analysis"]},{"i":"december-15-2010","l":"December 15, 2010","p":["Several new features, including:","Redesigned and streamlined user interface, based on user feedback and usability testing.","Advanced support for gene-specific alterations. For example, users can now view mutations within TP53, and ignore copy number alterations, or only view amplifications of EGFR, and ignore deletions.","Improved performance.","Frequently Asked Questions document released.","Updated Video Tutorial(update: old link no longer functional. Now see: YouTube"]},{"i":"november-4-2010","l":"November 4, 2010","p":["Enhanced Oncoprints, enabling users to quickly visualize genomic alterations across many cases. Oncoprints now also work in all major browsers, including Firefox, Chrome, Safari, and Internet Explorer.","Official release of our Web Interface, enabling programmatic access to all data.","Official release of our R Package, enabling programmatic access to all data from the R platform for statistical computing. OncoPrints"]}],[{"l":"Genie News"},{"i":"september-20-2023","l":"September 20, 2023","p":["Public Release 14.0 of AACR Project GENIE:","The first set of cancer genomic data aggregated through AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) was released to the global community in January 2017. The current release, GENIE 14.0-public now contains 183,000 sequenced samples from nearly 160,000 patients, making the AACR Project GENIE registry among the largest fully public cancer genomic data sets released to date.","More detailed information can be found in the AACR GENIE Data Guide. In addition to accessing the data via the cBioPortal, users can download the data directly from Sage Bionetworks. Users will need to create an account for either site and agree to the terms of access."]},{"i":"may-1-2023","l":"May 1, 2023","p":["Public Release 13.1 of AACR Project GENIE:","The public release 13.1 version of AACR GENIE has 65 samples retracted that were present in AACR GENIE 13.0-public.","More detailed information can be found in the AACR GENIE release notes and the data releases page from Sage Bionetworks"]},{"i":"january-9-2023","l":"January 9, 2023","p":["Public Release 13.0 of AACR Project GENIE:","The first set of cancer genomic data aggregated through AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) was released to the global community in January 2017. The current release, GENIE 13.0-public now contains more than 167,000 sequenced samples from over 148,000 patients, making the AACR Project GENIE registry among the largest fully public cancer genomic data sets released to date.","More detailed information can be found in the AACR GENIE Data Guide. In addition to accessing the data via the cBioPortal, users can download the data directly from Sage Bionetworks. Users will need to create an account for either site and agree to the terms of access."]},{"i":"november-3-2022","l":"November 3, 2022","p":["Public Release BPC CRC 2.0-PUBLIC","The GENIE BPC CRC v2.0-public dataset contains 1,485 CRC patients from three institutions: MSKCC, DFCI, and VICC.","The complete, post-processed data are available on Synapse"]},{"i":"july-6-2022","l":"July 6, 2022","p":["Public Release GENIE ERBB2 Cohort","The study contains 315 samples from 135 patients from 6 institues."]},{"i":"july-22-2022","l":"July 22, 2022","p":["Public Release 12.0 of AACR Project GENIE:","The first set of cancer genomic data aggregated through AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) was released to the global community in January 2017. The current release, GENIE 12.0-public, was released in July 2022.The registry now contains more than 154,000 sequenced samples from 137,000+ patients, making the AACR Project GENIE registry among the largest fully public cancer genomic data sets released to date.","More detailed information can be found in the AACR GENIE Data Guide. In addition to accessing the data via the cBioPortal, users can download the data directly from Sage Bionetworks. Users will need to create an account for either site and agree to the terms of access."]},{"i":"may-19-2022","l":"May 19, 2022","p":["Public Release BPC NSCLC 2.0-PUBLIC","The GENIE BPC NSCLC v2.0-public dataset contains 1,846 NSCLC patients from 4 institutions: MSKCC, DFCI, VICC and UHN.","The complete, post-processed data are available on Synapse"]},{"i":"january-7-2022","l":"January 7, 2022","p":["Public Release 11.0 of AACR Project GENIE:","The first set of cancer genomic data aggregated through AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) was released to the global community in January 2017. The current release, GENIE 11.0-public, was released in January 2022. The registry now contains over 136,000 sequenced samples from over 121,000 patients, making the AACR Project GENIE registry among the largest fully public cancer genomic data sets released to date.","More detailed information can be found in the AACR GENIE Data Guide. In addition to accessing the data via the cBioPortal, users can download the data directly from Sage Bionetworks. Users will need to create an account for either site and agree to the terms of access."]},{"i":"june-22-2021","l":"June 22, 2021","p":["Public Release 10.0 of AACR Project GENIE:","The first set of cancer genomic data aggregated through AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) was released to the global community in January 2017. The tenth data set, GENIE 10.0-public, was released in June 2021. With the most recent data release, the registry now contains genomic information from 120953 samples.","More detailed information can be found in the AACR GENIE Data Guide. In addition to accessing the data via the cBioPortal, users can download the data directly from Sage Bionetworks. Users will need to create an account for either site and agree to the terms of access."]},{"i":"february-8-2021","l":"February 8, 2021","p":["Public Release 9.0 of AACR Project GENIE:","The first set of cancer genomic data aggregated through AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) was released to the global community in January 2017. The ninth data set, GENIE 9.0-public, was released in February 2021. With the most recent data release, the registry now contains genomic information from more nearly 17,000 non-small cell lung carcinomas, and nearly 12,000 breast and more than 11,000 colorectal cancers.","More detailed information can be found in the AACR GENIE Data Guide. In addition to accessing the data via the cBioPortal, users can download the data directly from Sage Bionetworks. Users will need to create an account for either site and agree to the terms of access."]},{"i":"july-7-2020","l":"July 7, 2020","p":["Public Release 8.0 of AACR Project GENIE:","The first set of cancer genomic data aggregated through AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) was released to the global community in January 2017. The eighth data set, GENIE 8.0-public, was released in July 2020. The combined data set now includes nearly 96,000 de-identified genomic records collected from patients who were treated at each of the consortium's 19 participating institutions, making it among the largest fully public cancer genomic data sets released to date. The combined data set now includes data for over 80 major cancer types, including data from greater than 14,000 patients with lung cancer, nearly 12,000 patients with breast cancer, and nearly 9,500 patients with colorectal cancer.","More detailed information can be found in the AACR GENIE Data Guide. In addition to accessing the data via the cBioPortal, users can download the data directly from Sage Bionetworks. Users will need to create an account for either site and agree to the terms of access.","For frequently asked questions, visit the AACR FAQ page."]},{"i":"january-29-2020","l":"January 29, 2020","p":["Public Release 7.0 of AACR Project GENIE:","The first set of cancer genomic data aggregated through AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) was released to the global community in January 2017. The seventh data set, GENIE 7.0-public, was released in January 2020. The combined data set now includes nearly 79720 de-identified genomic records collected from patients who were treated at each of the consortium's participating institutions, making it among the largest fully public cancer genomic data sets released to date. The combined data set now includes data for over 80 major cancer types.","More detailed information can be found in the AACR GENIE Data Guide. In addition to accessing the data via the cBioPortal, users can download the data directly from Sage Bionetworks. Users will need to create an account for either site and agree to the terms of access.","For frequently asked questions, visit the AACR FAQ page."]},{"i":"july-13-2019","l":"July 13, 2019","p":["Public Release 6.1 of AACR Project GENIE:","The sixth data set, GENIE 6.0-public, was released in early July 2019. A patch to GENIE 6.0-public, GENIE 6.1-pubic, was subsequently released on July 13, 2019. The combined data set now includes nearly 70,000 de-identified genomic records collected from patients who were treated at each of the consortium's participating institutions, making it among the largest fully public cancer genomic data sets released to date. The combined data set now includes data for nearly 80 major cancer types, including data from nearly 11,000 patients with lung cancer, greater than 9,700 patients with breast cancer, and nearly 7,000 patients with colorectal cancer.","More detailed information can be found in the AACR GENIE Data Guide. In addition to accessing the data via the cBioPortal, users can download the data directly from Sage Bionetworks. Users will need to create an account for either site and agree to the terms of access.","For frequently asked questions, visit the AACR FAQ page."]},{"i":"july-08-2019","l":"July 08, 2019","p":["Public Release 6.0 of AACR Project GENIE:","The first set of cancer genomic data aggregated through AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) was released to the global community in January 2017. The sixth data set, GENIE 6.0-public, was released in July 2019 adding more than 11,000 records to the database. The combined data set now includes nearly 71,000 de-identified genomic records collected from patients who were treated at each of the consortium's participating institutions, making it among the largest fully public cancer genomic data sets released to date. The combined data set now includes data for over 80 major cancer types, including data from greater than 11,000 patients with lung cancer, nearly 9,800 patients with breast cancer, and more than 7,000 patients with colorectal cancer.","More detailed information can be found in the AACR GENIE Data Guide. In addition to accessing the data via the cBioPortal, users can download the data directly from Sage Bionetworks. Users will need to create an account for either site and agree to the terms of access.","For frequently asked questions, visit the AACR FAQ page."]},{"i":"january-11-2019","l":"January 11, 2019","p":["Public Release 5.0 of AACR Project GENIE:","The first set of cancer genomic data aggregated through AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) was released to the global community in January 2017. The forth data set, GENIE 4.0-public, was released in July 2018 adding more than 7,800 records to the database. The combined data set now includes more than 59,000 de-identified genomic records collected from patients who were treated at each of the consortium's participating institutions, making it among the largest fully public cancer genomic data sets released to date. This data will be released to the public every six months.","More detailed information can be found in the AACR GENIE Data Guide. In addition to accessing the data via the cBioPortal, users can download the data directly from Sage Bionetworks. Users will need to create an account for either site and agree to the terms of access.","For frequently asked questions, visit the AACR FAQ page."]},{"i":"july-16-2018","l":"July 16, 2018","p":["Public Release 4.0 of AACR Project GENIE:","The first set of cancer genomic data aggregated through AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) was released to the global community in January 2017. The forth data set, GENIE 4.0-public, was released in July 2018 adding more than 7,800 records to the database. The combined data set now includes more than 47,000 de-identified genomic records collected from patients who were treated at each of the consortium's participating institutions, making it among the largest fully public cancer genomic data sets released to date. This data will be released to the public every six months. The public release of the fifth data set, GENIE 5.0-public, will take place in January, 2019.","The combined data set now includes data for over 80 major cancer types, including data from greater than 7,500 patients with lung cancer, nearly 5,500 patients with breast cancer, and more than 5,100 patients with colorectal cancer.","More detailed information can be found in the AACR GENIE Data Guide. In addition to accessing the data via the cBioPortal, users can download the data directly from Sage Bionetworks. Users will need to create an account for either site and agree to the terms of access.","For frequently asked questions, visit the AACR FAQ page."]},{"l":"January 2018","p":["Added 7500 samples to the GENIE Public Cohort The combined dataset now includes samples from over 60 major cancer types including:","6,000 lung cancer samples.","4,500 breast cancer samples.","4,300 colorectal cancer samples.","More detailed information can be found in the AACR GENIE Data Guide. In addition to accessing the data via the cBioPortal, users can download the data directly from Sage Bionetworks. For frequently asked questions, visit the AACR FAQ page."]},{"i":"november-20-2017","l":"November 20, 2017","p":["Public Release 2.0 of AACR Project GENIE:","The first set of cancer genomic data aggregated through AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) was released to the global community in January 2017. The second dataset was released in November 2017, adding more than 13,000 records to the database. The combined data set now includes over 32,000 de-identified genomic records collected from patients who were treated at each of the consortium’s participating institutions, making it among the largest fully public cancer genomic data sets released to date. These data will be continuously updated on a quarterly basis.","The combined data set now includes data for 59 major cancer types, including data on nearly 5,000 patients with lung cancer, nearly 4,000 patients with breast cancer, and more than 3,500 patients with colorectal cancer. For more details about the data, and how to use it, consult the data guide.","In addition to accessing the data on the AACR Project GENIE cBioPortal website, users can download the data directly from Sage Bionetworks. Users will need to create an account for either site and agree to the terms of access.","For frequently asked questions, visit the AACR FAQ page."]},{"i":"january-5-2017","l":"January 5, 2017","p":["Initial public release of AACR Project GENIE:","Somatic alterations in 18,980 tumor samples from 18,500 patients sequenced at eight different institutions.","Data is available for download from Sage Bionetworks."]},{"l":"AACR Project GENIE cBioPortal Terms of Use","p":["I will not attempt to identify or contact individual participants from whom these data were collected by any means.","I will not redistribute the data without express written permission from the AACR Project GENIE Coordinating Center (info at aacrgenie dot org).","When publishing or presenting work using or referencing the AACR Project GENIE dataset please include the following attributions:","Please cite: AACR Project GENIE Consortium. AACR Project GENIE: Powering Precision Medicine Through an International Consortium, Cancer Discov. 2017 Aug;7(8):818-831 and include the version of the dataset used.","Include the following acknowledgement: The authors would like to acknowledge the American Association for Cancer Research and its financial and material support in the development of the AACR Project GENIE registry, as well as members of the consortium for their commitment to data sharing. Interpretations are the responsibility of study authors.","Should you decide at any point in the future to stop using the AACR Project GENIE cBioPortal, send request: genie-cbioportal-access at cbio dot mskcc dot org and we will remove your user id and any other information provided during new user registration from our systems.","For more information see terms of access on the AACR website."]}],[{"l":"API and API Clients","p":["cBioPortal provides a REST API for programmatic access to the data. The visualizations one can see on the website leverage the same API. By connecting to the API directly, anyone can build their own visalizations/reports.","Please see the full reference documentation for the API here."]},{"l":"API Clients","p":["The cBioPortal REST API is described using Swagger/OpenAPI, which allows one to generate a client in most programming languages. One can use the command line tool curl for dowloading data on the command line or use another language such as Python or R to make visualizations. We list some common examples below, but if your language is not listed, there is likely a client generator available elsewhere (see e.g. https://swagger.io/tools/swagger-codegen/). Do reach out if you'd like us to add a language."]},{"l":"R clients","p":["There are multiple ways to access the API using R. Below are two recommended R packages to access cBioPortal data."]},{"i":"cbioportaldata-recommended","l":"cBioPortalData (recommended)","p":["cBioPortalData aims to import all cBioPortal datasets as MultiAssayExperiment objects in Bioconductor. Some of its key features:","The MultiAssayExperiment class explicitly links all assays to the patient clinical/pathological data","The MultiAssayExperiment class provides a flexible API including harmonized subsetting and reshaping to convenient wide and long formats.","It provides complete datasets, not just for subsets of genes","It provides automatic local caching, thanks to BiocFileCache.","For a comprehensive user guide to cBioportalData see: https://waldronlab.io/cBioPortalData/articles/cBioPortalData.html","See also the workshop materials from our webinar which include an intro to cBioPortalData: https://github.com/cBioPortal/2020-cbioportal-r-workshop.","Note that one can point to private authenticated instances like this:"]},{"i":"cbioportalr-recommended","l":"cbioportalR (recommended)","p":["cbioportalR offers easy-to-use functions that allow users to browse and pull data from public or institutional cBioPortal sites without knowledge of web service or Bioconductor infrastructures. The package is tidyverse-compatible. Key package features include:","Comprehensive documentation aimed at helping clinical researchers understand the underlying structure of cBioPortal data","Tutorials for quick API authentication and set up","Functions to pull complete clinical and genomic data by study ID, molecular profile ID, sample list IDs or individual sample ID (e.g. get_genetics_by_study(), get_genetics_by_sample())","Functions to navigate and identify patient IDs, sample IDs or study IDs as needed, or infer necessary ID information for queries when not supplied by user.","Helper functions to pull information on gene panels ( get_gene_panel()), or lookup entrez ID ( get_entrez_id()), Hugo Symbol ( get_hugo_symbol()) or common gene aliases ( get_alias()) of genes","Capability to query multiple sample IDs from different studies concurrently","For a detailed tutorial on cbioportalR, see the package website: https://www.karissawhiting.com/cbioportalR/articles/overview-of-workflow.html"]},{"l":"rapiclient","p":["Although we recommend cBioPortalData or cbioportalR for most use cases, it is possible to connect to the API directly using rapiclient:"]},{"i":"cgdsr-will-be-deprecated","l":"CGDSR (will be deprecated)","p":["The CGDS-R package connects an older version of our web API ( webservice.do). Althought we will continue to keep webservice.do running for a while, we can't guarantee the same level of quality as our new API ( cbioportal.org/api) provides. Therefore we recommend that you use cBioPortalData instead."]},{"l":"Python client","p":["There are multiple ways to access the API using Python. One can use the bravado package to access the API directly, or use the cbio_py client, which provides a simple wrapper for the API and returns data in a format that is easy to work with."]},{"l":"bravado","p":["Generate a client in Python using bravado like this:","This allows you to access all API endpoints:","For easy tab completion you can add lower cases and underscores:","This example gets you all mutation data for the MSK-IMPACT 2017 study:","For a portal that requires authentication one can use (see Data Access Using Tokens):","A Jupyter notebook with more examples can be found here."]},{"l":"cbio_py","p":["See the cbio_py documentation: https://pypi.org/project/cbio-py/."]}],[{"l":"Deployment","p":["Private instances of cBioPortal are maintained by institutions and companies around the world.","An instance can be deployed using Docker (recommended) or by building and deploying from source. The source code of cBioPortal is available on GitHub under the terms of Affero GPL V3.","This section contains instructions for both of these paths.","Please note that installing a local version requires system administration skills; for example, installing and configuring Tomcat and MySQL. With limited resources, we cannot provide technical support on system administration."]}],[{"l":"Architecture Overview","p":["cBioPortal consists of the following components:","backend","MySQL database","REST API written in Java Spring","Redis cache for storing frequently used queries (optional)","validator checks file formats before importing data into the database","frontend built with React, Mobx and Bootstrap","session service for storing user saved data such as virtual studies and groups","REST API written in Java Spring enabling retrieval and writing to the database","MongoDB database","cBioPortal also uses the APIs from various external services to provide more information about a variant"]},{"l":"Backend","p":["The backend is written in Java and connects to a MySQL database to serve a REST API following the OpenAPI specification ( https://www.cbioportal.org/api/). Note that the repo where this lives in ( https://github.com/cBioPortal/cbioportal) also contains Java classes to import data as well as the validator. The backend can be configured to connect to a Redis cache to store database query results for improved performance.","The backend is organized as a multi-module Maven project. See cBioPortal backend code organization."]},{"l":"Validator","p":["The validator checks file formats before importing data into the database. There is a wrapper script metaImport.py that validates the data and subsequently calls the relevant Java classes to import the data."]},{"l":"Session Service","p":["The session service is used for storing user saved data such as virtual studies and groups. See the tutorials section to read more about these features. Session service is a Java app that serves a REST API backed by a Mongo database. The session service is served as a proxy through the cBioPortal backend REST API. The backend is therefore the only component that needs to be able to connect to it. The frontend does not connect to it directly."]},{"l":"Frontend","p":["The frontend is a single page app built with React, Mobx and Bootstrap. The data gets pulled from the backend REST API. The frontend is by default included with the backend so no extra setup is required."]},{"l":"External Services","p":["cBioPortal uses the APIs from several external services to provide more information about a variant:","OncoKB","CIVIC","Genome Nexus","G2S","For privacy concerns see the section: A note on privacy."]},{"l":"OncoKB","p":["OncoKB is a precision oncology knowledge base that contains information about the effects and treatment implications of specific cancer gene alterations. See the section OncoKB Data Access for how to configure external OncoKB service."]},{"l":"CIVIC","p":["CIVIC is a community-edited forum for discussion and interpretation of peer-reviewed publications pertaining to the clinical relevance of variants (or biomarker alterations) in cancer. For information on how to deploy this service yourself see: https://github.com/griffithlab/civic-server. It is also possible to disable showing CIVIC in cBioPortal by setting show.civic=false in the portal.properties(See portal.properties reference)."]},{"l":"Genome Nexus","p":["Genome Nexus is a comprehensive one-stop resource for fast, automated and high-throughput annotation and interpretation of genetic variants in cancer. For information on how to deploy this service yourself see: https://github.com/genome-nexus/genome-nexus. For more information on the various annotation sources and versions provided by Genome Nexus see: https://docs.genomenexus.org/annotation-sources."]},{"l":"G2S","p":["G2S (Genome to Structure) maps genomic variants to 3D structures. cBioPortal uses it on the mutations tab to show the variants on a 3D structure. For information on how to deploy this service yourself see: https://github.com/genome-nexus/g2s."]},{"l":"A note on privacy","p":["cBioPortal calls these services with variant information from the cBioPortal database. It however does not send over information that links a variant to a particular sample or patient. If this is a concern for your use case we recommmend to deploy your own versions of these services. See the sections above to linkouts for instructions on how to do this."]}],[{"l":"Hardware Requirements","p":["Hardware requirements will vary depending on the volume of users you anticipate will access your cBioPortal instance and the amount of data loaded in the portal. We run cbioportal.org on an AWS r5.xlarge instance with 32 GB and 4 vCPUs. The public database consumes ~ 50 GB of disk space. The site is visited by several thousands of users a day. For on-premise installation recommendations one can look at the AWS instance type specs:","Platform","instance type","(v)CPUs","RAM(GB)","Storage (GB)","aws","r5.xlarge","4","32","50","on-premise","-","The hardware requirements are much lower when one has only a few users a day. Minimally, 2GB of RAM is needed to run a cBioPortal instance. If you do not plan to import public studies, depending on the size of your private data, 10GB of disk space may be sufficient.","Another possible consideration is caching. The portal can cache responses to requests so that repeated database queries are avoided. On the public cBioPortal deployment we enable this cache and allocate 1GB of additional RAM and 4GB of additional disk space for caching. For directions on configuring caching, see Ehcache Settings"]}],[{"l":"Deploy with Docker"},{"l":"Prerequisites","p":["Docker provides a way to run applications securely isolated in a container, packaged with all its dependencies and libraries. To learn more on Docker, kindly refer here: Docker overview.","Make sure that you have the latest version of Docker installed on your machine. Get latest version","Notes for non-Linux systems"]},{"l":"Usage instructions","p":["In this example we use Docker Compose to spin up all the different required containers/services for cBioPortal."]},{"l":"Quick Start","p":["You should now be able to see the cBioPortal website at http://localhost:8080","Import studies with:","Clear persistent data volumes with:"]},{"l":"Comprehensive Start"},{"i":"step-1---run-docker-compose","l":"Step 1 - Run Docker Compose","p":["Download the git repo that has the Docker compose file and go to the root of that folder:","Then download all necessary files (seed data, example config and example study from datahub) with the init script:","Then run:","This will start all four containers (services) defined here. That is:","the mysql database, which holds most of the cBioPortal data","the cBioPortal Java web app, this serves the React frontend as well as the REST API","the session service Java web app. This service has a REST API and stores session information (e.g. what genes are being queried) and user specific data (e.g. saved cohorts) in a separate mongo database","the mongo database that persists the data for the session service","It will take a few minutes the first time to import the seed database and perform migrations if necessary. Each container outputs logs to the terminal. For each log you'll see the name of the container that outputs it (e.g. cbioportal_container or cbioportal_session_database_container). If all is well you won't see any significant errors (maybe some warnings, that's fine to ignore). If all went well you should be able to visit the cBioPortal homepage on http://localhost:8080. You'll notice that no studies are shown on the homepage yet:","Go to the next step to see how to import studies."]},{"l":"Notes on detached mode","p":["If you prefer to run the services in detached mode (i.e. not logging everything to your terminal), you can run","In this mode, you'll have to check the logs of each container manually using e.g.:","You can list all containers running on your system with"]},{"i":"step-2---import-studies","l":"Step 2 - Import Studies","p":["To import studies you can run:","This will import the lgg_ucsf_2014 study into your local database. It will take a few minutes to import. After importing, restart the cbioportal web container:","or","All public studies can be downloaded from https://www.cbioportal.org/datasets, or https://github.com/cBioPortal/datahub/. You can add any of them to the ./study folder and import them. There's also a script (./study/init.sh) to download multiple studies. You can set DATAHUB_STUDIES to any public study id (e.g. lgg_ucsf_2014) and run ./init.sh."]},{"l":"Notes on restarting","p":["To avoid having to restart one can alternatively hit an API endpoint. To do so, call the /api/cache endpoint with a DELETE http-request (see here for more information):","The value of the API key is configured in the portal.properties file. You can visit http://localhost:8080 again and you should be able to see the new study."]},{"i":"step-3---customize-your-portalproperties-file","l":"Step 3 - Customize your portal.properties file","p":["The properties file can be found in ./config/portal.properties. Which was set up when running init.sh.","This properties file allows you to customize your instance of cBioPortal with e.g. custom logos, or point the cBioPortal container to e.g. use an external mysql database. See the properties documentation for a comprehensive overview.","If you would like to enable OncoKB see OncoKB data access for how to obtain a data access token. After obtaining a valid token use:"]},{"i":"step-4---customize-cbioportal-setup","l":"Step 4 - Customize cBioPortal setup","p":["To read more about the various ways to use authentication and parameters for running the cBioPortal web app see the relevant backend deployment documentation.","On server systems that can easily spare 4 GiB or more of memory, set the -Xms and -Xmx options to the same number. This should increase performance of certain memory-intensive web services such as computing the data for the co-expression tab. If you are using MacOS or Windows, make sure to take a look at these notes to allocate more memory for the virtual machine in which all Docker processes are running."]},{"l":"More commands","p":["For documentation on how to import a study, see this tutorial For more uses of the cBioPortal image, see this file","To Dockerize a Keycloak authentication service alongside cBioPortal, see this file."]},{"l":"Uninstalling cBioPortal"}],[{"l":"Import data with Docker"},{"l":"Import data instructions","p":["This is an example to import a sample study: study_es_0. When trying to import other studies, please follow the same routine:","import gene panels (if applicable, studies without gene panels are assumed to be whole exome/genome)","import study data"]},{"i":"step-1---import-gene-panels","l":"Step 1 - Import gene panels","p":["To import gene panels for your study, please reference the example commands in this file","These are the commands for importing study_es_0 gene panels ( data_gene_panel_testpanel1 and data_gene_panel_testpanel2):"]},{"i":"step-2---import-data","l":"Step 2 - Import data","p":["To import data for your study, please reference the example commands in this file","Command for importing study_es_0 data:","⚠️ after importing a study, remember to restart cbioportal to see the study on the home page. Run docker-compose restart cbioportal.","You have now imported the test study study_es_0. Note that this study is included inside the cbioportal container. The process for adding a study that is outside of the container is similar. Just make sure to add the data files in the ./study folder. This folder is mounted as /study/ inside of the container."]},{"l":"Frequently Asked Questions"},{"l":"Gene panel ID is not in database","p":["If you see an error like this when you importing the data: ERROR: data_gene_panel_matrix.txt: lines [2, 3, 4, (10 more)]: Gene panel ID is not in database. Please import this gene panel before loading study data.; values encountered: ['TESTPANEL1', 'TESTPANEL2']","please follow the first step to import gene panels (e.g. import data_gene_panel_testpanel1 and data_gene_panel_testpanel2 for study_es_0), then try to import the data again."]},{"l":"Error occurred during validation step","p":["Please make sure the seed database was correctly imported."]},{"i":"study-imported-correctly-but-got-error-when-trying-to-query-something","l":"Study imported correctly, but got error when trying to query something","p":["Remember to restart the cbioportal after data imported."]},{"l":"Import GRCh38 data","p":["If you are importing GRCh38 data, please remember to set the reference_genome: hg38 field in the meta_study.txt file. See also cancer study metadata."]}],[{"l":"Example commands"},{"l":"Importing gene panel","p":["Use this command to import a gene panel. Specify the gene panel file by replacing path_to_genepanel_file with the absolute path to the gene panel file. Another option is to add the gene panel files in ./study which is mounted inside the container on `/study/."]},{"l":"Importing data","p":["Use this command to validate a dataset. Add the study to the ./study folder. The command will connect to the web API of the container cbioportal-container, and import the study in its associated database. Make sure to replace path_to_report_folder with the absolute path were the html report of the validation will be saved.","⚠️ after importing a study, remember to restart cbioportal-container to see the study on the home page. Run docker-compose restart cbioportal."]},{"l":"Using cached portal side-data","p":["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. Make sure to replace path_to_portalinfo with the absolute path where the cached folder is going to be generated.","Then, grant the validation/loading command access to this folder and tell the script it to use it instead of the API:"]},{"l":"Inspecting or adjusting the database"},{"l":"Deleting a study","p":["To remove a study, run:","Where study_id is the cancer_study_identifier of the study you would like to remove."]}],[{"l":"Authenticating and Authorizing Users using Keycloak in Docker","p":["This guide describes a way to Dockerise Keycloak along with cBioPortal, for authentication.","First, create an isolated network in which the Keycloak and MySQL servers can talk to one another.","Run a MySQL database in which Keycloak can store its data. This database server will not be addressable from outside the Docker network. Replace path_to_database with the absolute path where the folder kcdb-files will be placed. This folder is used by the database to store its files.","Then run the actual Keycloak server, using this image available from Docker Hub. This will by default connect to the database using the (non-root) credentials in the example above. The server will be accessible to the outside world on port 8180, so make sure to choose a strong administrator password.","The command below uses the default values for MYSQL_DATABASE, MYSQL_USER and MYSQL_PASSWORD(listed in the command above). If you wish to change these credentials, specify them in the command below. For instance, if MYSQL_USER in the database container is user, you need to add -e MYSQL_USER=user.","Finally, configure Keycloak and cBioPortal as explained in the Keycloak documentation. Remember to specify port 8180 for the Keycloak server, wherever the guide says 8080.","After configuring Keycloak, set up cBioPortal containers as specified in the documentation. Make sure to update the -Dauthenticate in the docker-compose file to -Dauthenticate=saml."]}],[{"l":"Software Requirements","p":["This page describes various system software required to run the cBioPortal."]},{"l":"MySQL","p":["The cBioPortal software should run properly on MySQL version 5.7.x. Versions higher than 5.7.x can cause an issue while loading the database schema. Minor versions lower than 5.7.x will cause issues with persistent cache invalidation. The software can be found and downloaded from the MySQL website.","On Ubuntu: sudo apt-get install mysql-server"]},{"l":"MongoDB","p":["The session service uses MongoDB 3.6.6"]},{"l":"Java","p":["As of this writing, the cBioPortal can be compiled and run from Java 11 and above. The software can be found and download from the Oracle website.","On Ubuntu: sudo apt-get install default-jdk"]},{"l":"Apache Maven","p":["The cBioPortal source code is an Apache Maven driven project. The software needs to be downloaded and installed prior to building the application from source code. It can be found on the Apache Maven website. We are currently using version 3.5.4.","On Ubuntu: sudo apt-get install maven"]},{"l":"Git","p":["You will need a git client to download the cBioPortal source code.","On Ubuntu: sudo apt-get install git"]}],[{"l":"Pre-Build Steps"},{"l":"Get the Latest Code","p":["Make sure that you have cloned the last code, and make sure you are on the master branch:"]},{"i":"prepare-the-log4jproperties-file","l":"Prepare the log4j.properties File","p":["This file configures logging for the portal. An example file is available within GitHub:","If you don't create your own logback.xml, maven will copy the EXAMPLE file to that location when it builds. If logback.xml already exists, it will just use that. This allows us to give you a working, versioned log config, which you can then override easily.","To modify the logging during tests the same EXAMPLE file can be copied to the relevant test resources folder."]},{"l":"Create the cBioPortal MySQL Databases and User","p":["You must create a cbioportal database and a cgds_test database within MySQL, and a user account with rights to access both databases. This is done via the mysql shell."]}],[{"l":"Building from Source"},{"l":"Building with Maven","p":["While building, you must point the environment variable PORTAL_HOME to the root directory containing the portal source code.","For example, run a command like the following if on macOS:","To compile the cBioPortal source code, move into the source directory and run the following maven command:","After this command completes, you will find a cbioportal.war file suitable for Apache Tomcat deployment in portal/target/. It is not neccessary to install Tomcat yourself, since a command line runnable version of Tomcat is provided as a dependency in portal/target/dependency/webapp-runner.jar.","However, if you will be deploying to a standalone Tomcat installation, and if you have configured Tomcat to use the Redisson client for user session management, you should expect a clash between the Redisson client being used for session management and the Redisson client which is embedded in the cbioportal.war file for the optional \"redis\" persitence layer caching mode. In this case, you should avoid using the \"redis\" option for the portal property persistence.cache_type and you should prevent the Redisson client from being packaged in cbioportal.war by building with this command instead:"]},{"l":"alternative for standalone tomcat deployments which use redis session management"}],[{"l":"Importing the Seed Database","p":["The next step is to populate your cBioPortal instance with all the required background data sets. This includes for example gene data, ID mappings, and network interactions. Rather than importing each of these data sets individually, we have provided a simple \"seed\" database that you can import directly."]},{"l":"Download the cBioPortal Seed Database","p":["A cBioPortal seed database for human can be found on the datahub page. If you are looking for mouse, check this link.","After download, the files can be unzipped by entering the following command:"]},{"l":"Import the cBioPortal Seed Database","p":["Important: Before importing, make sure that you have followed the pre-build steps for creating the cbioportal database (see section \"Create the cBioPortal MySQL Databases and User\").","Import the database schema (/db-scripts/src/main/resources/cgds.sql):","Note that this may currently fail when using the default character encoding on MySQL 8.0 ( utf8mb4); this is why MySQL 5.7 (which uses latin1) is recommended.","Import the main part of the seed database:","Important: Replace seed-cbioportal_RefGenome_vX.Y.Z.sql with the downloaded version of the seed database, such as seed-cbioportal_hg19_v2.3.1.sql or seed-cbioportal_mm10_v2.3.1.sql.","(Human only) Import the Protein Data Bank (PDB) part of the seed database. This will enable the visualization of PDB structures in the mutation tab. Loading this file takes more time than loading the previous files, and is optional for users that do not require PDB structures.","Important: Replace seed-cbioportal_hg19_vX.Y.Z_only-pdb.sql with the downloaded version of the PDB database, such as seed-cbioportal_hg19_v2.3.1_only-pdb.sql.","(optional : support for microRNA genomic profiles) Import constructed gene table records for microRNA genomic profiles. Currently, cBioPortal supports the combined display of copy number alterations (generally reported for microRNA precursors) and expression (generally reported for microRNA mature forms) by adding gene table records which represent the combination of microRNA precursor and microRNA mature form. Appropriate aliases are added to the gene_alias table so that both the name of the precursor and the name of the mature form are recognized references to the combination.","After the code has been successfully configured and built, you can import the needed microRNA records by running the following command from the $PORTAL_HOME directory:","Important: Please be aware of the version of the seed database. In the README on datahub, we stated which version of cBioPortal is compatible with the current seed database.","If the database is older than what cBioPortal is expecting, the system will ask you (during startup or data loading) to migrate the database to a newer version. The migration process is described here."]}],[{"l":"Deploying the Web Application"},{"l":"Prepare the global configuration file","p":["The portal is configured using a global configuration file, portal.properties. An example file is available in the src/main/resources folder. Use it as a template to create your own:","For more information about the portal.properties file, see the reference page.","Several scripts of cBioPortal use this portal.properties file to get info like db connection parameters. You can indicate the folder where this file is with an environment variable:","if your properties file is at PORTAL_HOME/portal.properties"]},{"l":"Run cBioPortal Session Service","p":["The cBioPortal app requires session service. For instructions on how to run this without Docker see https://github.com/cBioPortal/session-service#run-without-docker. Once this is working, update the properties file:"]},{"l":"Run the cbioportal backend","p":["To run the app we use webapp-runner. It's a command line version of Tomcat provided by Heroku. All parameters can be seen with:","This runs the app in the foreground. If a port is already in use it will raise an error mentioning that. To change the port use the --port flag.","There are three main ways to run the portal: without authentication, with optional login and with required login. All of them require the cBioPortal session service to be running."]},{"l":"Without authentication","p":["In this mode users are able to use the portal, but they won't be able to save their own virtual studies and groups. See the optional login section to enable this."]},{"l":"Optional login","p":["In this mode users can see all the data in the portal, but to save their own groups and virtual studies they are required to log in. This will allow them to store user data in the session service. See the tutorials section to read more about these features.","Google and Microsoft live are supported as optional login currently. Possible values for authenticate are","One needs to set the Google/Microsoft related configurations in the portal.properties file:","See Google's Sign in Documentation to obtain these values.","See Microsoft Sign in Documentation to obtain these values."]},{"l":"Required login","p":["Change CHOOSE_DESIRED_AUTHENTICATION_METHOD to one of googleplus, saml, openid, ad, ldap. The various methods of authentication are described in the Authorization and Authentication section."]},{"l":"Property configuration","p":["The configuration defined in portal.properties can also be passed as command line arguments. The priority of property loading is as follows:","-D command line parameters overrides all","${PORTAL_HOME}/portal.properties","portal.properties supplied at compile time","Defaults defined in code","Note that the authenticate property is currently required to be set as a command line argument, it won't work when set in portal.properties(See issue #6109).","Some scripts require a ${PORTAL_HOME}/portal.properties file, so it is best to define the properties there."]},{"l":"Note for Tomcat Deployers","p":["Before we were using webapp-runner, our documentation recommended a system level installed Tomcat. In this case people might have been using dbconnector=jndi instead of the new default dbconnector=dbcp. There is a known issue where setting dbconnector in the properties file does not work (#6148). It needs to be set as a command line argument. For Tomcat this means CATALINA_OPT=-Ddbconnector=jndi."]},{"l":"Verify the Web Application","p":["Lastly, open a browser and go to: http://localhost:8080"]},{"l":"Important","p":["Each time you modify any java code, you must recompile and redeploy the app.","Each time you modify any properties (see customization options), you must restart the app","Each time you add new data, you must restart the app or call the /api/cache endpoint with a DELETE http-request (see here for more information)."]}],[{"l":"Loading a Sample Study","p":["Once you have confirmed that the cBioPortal server is installed, you are ready to import data. Importing a sample study is recommended to verify that everything is working correctly.","The cBioPortal distribution includes a small dummy study, study_es_0, which contains all datatypes supported by cBioPortal. This document describes how to import the prerequisites for the sample study and how to import the study itself."]},{"l":"Set the PORTAL_HOME environment variable","p":["Most cBioPortal command-line tools, including the data loading pipeline, expect the environment variable $PORTAL_HOME to point to a folder containing the portal.properties configuration file, as explained during the previous step.","Configure your shell to keep the variable set to the right folder. On GNU/Linux and macOS this usually means appending a line like the following to .bash_profile in your home directory:"]},{"l":"Import Gene Panel for Sample Study","p":["The sample gene panel has to be imported before gene panel study data can be added to the database.","After loading gene panels into the database, please restart Tomcat or call the /api/cache endpoint with a DELETE http-request(see here for more information) so that the validator can retrieve gene panel information from the cBioPortal API.","More details to load your own gene panel and gene set data can be found here: Import Gene Panels."]},{"l":"Validating the Sample Study","p":["First it's useful to validate the study study_es_0, to check if the data is formatted correctly.","To do so, go to the importer folder:","and then run the following command:","If all goes well, you should see the final output message:"]},{"l":"Importing the Sample Study","p":["To import the sample study:","and then run the following command:","You will see a series of output messages, hopefully ending with a status message like this:","After loading the study data, please restart the app or call the /api/cache endpoint with a DELETE http-request(see here for more information)."]}],[{"l":"User Authorization","p":["This step is only required if you intend on running an instance of the portal that supports user authorization.","Two tables need to be populated in order to support user authorization."]},{"i":"table--users","l":"Table: users","p":["This table contains all the users that have authorized access to the instance of the portal. The table requires a user's email address, name, and integer flag indicating if the account is enabled.","An example entry would be:","Note, if the ENABLED value is set to 0, the user will be able to login to the portal, but will see no studies.","You need to add users via MySQL directly. For example:"]},{"i":"table--authorities","l":"Table: authorities","p":["This table contains the list of cancer studies that each user is authorized to view. The table requires a user email address and an authority (e.g. cancer study) granted to the user.","Some example entries would be:","The value in the EMAIL column should be the same email address contained in the USER table.","The value in the AUTHORITY column is made of two parts:","The first part is the name of your portal instance. This name should also match the app.name property found in the portal.properties file.","Following a colon delimiter, the second part is the cancer_study_identifier of the cancer study this user has rights to access.","If the user has rights to all available cancer studies, a single entry with the keyword app.name: + \"ALL\" is sufficient (so e.g. \"cbioportal:ALL\").","You need to add users via MySQL directly. For example:","Important Note: The cancer study identifier is not CASE sEnsitive. So it can be UPPER CASE, or just how it is stored in the cancer_study table. Changes to these tables become effective the next time the user logs in."]},{"l":"Using groups","p":["It is also possible to define groups and assign multiple studies and users to a group. You can add a group name to the cancer_study table GROUPS column. This same group name can be used in the AUTHORITY column of the authorities table mentioned above."]},{"i":"example","l":"Example:","p":["We want to create the group \"TEST_GROUP1\" and assign two existing studies to it and give our user 'john.smith@gmail.com' access to this group of studies. Steps:","1- Find your studies in table cancer_study","2- Update the GROUPS field, adding your \"TEST_GROUP1\" to it. ⚠️ This is a ; separated column, so if you want a study to be part of multiple groups, separate them with ;.","If GROUPS already has a value (like for study 93 in example above) then add \";TEST_GROUP1\" to ensure existing groups are not ovewritten.","3- Check the result:","4- Add the group to user 'john.smith@gmail.com', using app.name:+ \"TEST_GROUP1\" like so:","After next login, the user 'john.smith@gmail.com' will have access to these two studies."]},{"l":"Configuring PUBLIC studies","p":["To enable a set of public studies that should be visible to all users, without the need to configure this for each user in the authorities and users tables, you can set the property always_show_study_group in portal.properties file. For example, you can set:","This will enable the word \"PUBLIC\" to be used in the column GROUPS of the table cancer_study to indicate which studies should be always shown to any authenticated user, regardless of authorization configurations."]},{"i":"example-1","l":"Example:","p":["To reuse the example table above, let's assume the property always_show_study_group is set as indicated above and the cancer_study table contents are set to the following:","In this case, the study brca_tcga will be visible to any authenticated user while the study acc_tcga will be visible only to users configured to be part of GROUPB or TEST_GROUP1"]}],[{"l":"Introduction","p":["The cBioPortal includes support for SAML (Security Assertion Markup Language). This document explains why you might find SAML useful, and how to configure SAML within your own instance of cBioPortal.","Please note that configuring your local instance to support SAML requires many steps. This includes configuration changes and a small amount of debugging. If you follow the steps below, you should be up and running relatively quickly, but be forewarned that you may have do a few trial runs to get everything working.","In the documentation below, we also provide details on how to perform SAML authentication via a commercial company: OneLogin. OneLogin provides a free tier for testing out SAML authentication, and is one of the easier options to get a complete SAML workflow set-up. Once you have OneLogin working, you should then have enough information to transition to your final authentication service."]},{"i":"what-is-saml","l":"What is SAML?","p":["SAML is an open standard that enables one to more easily add an authentication service on top of any existing web application. For the full definition, see the SAML Wikipedia entry.","In its simplest terms, SAML boils down to four terms:","identity provider: this is a web-based service that stores user names and passwords, and provides a login form for users to authenticate. Ideally, it also provides easy methods to add / edit / delete users, and also provides methods for users to reset their password. In the documentation below, OneLogin.com serves as the identity provider.","service provider: any web site or web application that provides a service, but should only be available to authenticated and authorized users. In the documentation below, the cBioPortal is the service provider.","authentication: a means of verifying that a user is who they purport to be. Authentication is performed by the identify provider, by extracting the user name and password provided in a login form, and matching this with information stored in a database. When authentication is enabled, multiple cancer studies can be stored within a single instance of cBioPortal while providing fine-grained control over which users can access which studies. Authorization is implemented within the core cBioPortal code, and not the identify provider."]},{"i":"why-is-saml-relevant-to-cbioportal","l":"Why is SAML Relevant to cBioPortal?","p":["The cBioPortal code has no means of storing user name and passwords and no means of directly authenticating users. If you want to restrict access to your instance of cBioPortal, you therefore have to consider an external authentication service. SAML is one means of doing so, and your larger institution may already provide SAML support. For example, at Sloan Kettering and Dana-Farber, users of the internal cBioPortal instances login with their regular credentials via SAML. This greatly simplifies user management."]},{"l":"Setting up an Identity Provider","p":["As noted above, we provide details on how to perform SAML authentication via a commercial company: OneLogin. If you already have an IDP set up, you can skip this part and go to Configuring SAML within cBioPortal.","OneLogin provides a free tier for testing out SAML authentication, and is one of the easier options to get a complete SAML workflow set-up. Once you have OneLogin working, you should then have enough information to transition to your final authentication service. As you follow the steps below, the following link may be helpful: How to Use the OneLogin SAML Test Connector.","To get started:","Register a new OneLogin.com Account"]},{"l":"Setting up a SAML Test Connector","p":["\"SAVE\" the app, then select the Configuration Tab.","ACS (Consumer) URL Validator*: ^ http://localhost:8080/cbioportal/saml/SSO$","ACS (Consumer) URL*: http://localhost:8080/saml/SSO","Add at least the parameters:","Audience: cbioportal","Configure these email parameters in the Users menu:","Email (Attribute)","Email (SAML NameID)","Find your user in the \"Users\" menu","Link the SAML app to your user (click \"New app\" on the + icon found on the top right of the \"Applications\" table to do this - see screenshot below):","Login to OneLogin.com.","Recipient: http://localhost:8080/saml/SSO","Search for SAML.","Select the option labeled: OneLogin SAML Test (IdP w/attr).","Under Apps, Select Add Apps.","Under the Configuration Tab for OneLogin SAML Test (IdP w/attr), paste the following fields (this is assuming you are testing everything via localhost)."]},{"l":"Downloading the SAML Test Connector Meta Data","p":["Go to the SSO Tab within OneLogin SAML Test (IdP), find the field labeled: Issuer URL. Copy this URL and download it's contents. This is an XML file that describes the identity provider.","then, move this XML file to:","You should now be all set with OneLogin.com. Next, you need to configure your instance of cBioPortal."]},{"l":"Configuring SAML within cBioPortal"},{"l":"Creating a KeyStore","p":["In order to use SAML, you must create a Java Keystore.","This can be done via the Java keytool command, which is bundled with Java.","Type the following:","This will create a Java keystore for a key called: secure-key and place the keystore in a file named samlKeystore.jks. You will be prompted for:","keystore password (required, for example: apollo1)","your name, organization and location (optional)","key password for secure-key(required, for example apollo2)","When you are done, copy samlKeystore.jsk to the correct location:","If you need to export the public certificate associated within your keystore, run:"]},{"l":"HTTPS and Tomcat","p":["⚠️ If you already have an official (non-self-signed) SSL certificate, and need to get your site running on HTTPS directly from Tomcat, then you need to import your certificate into the keystore instead. See this Tomcat documentation page for more details.","⚠️ An extra warning for when configuring HTTPS for Tomcat: use the same password for both keystore and secure-key. This seems to be an extra restriction by Tomcat."]},{"l":"Modifying configuration","p":["Within portal.properties, make sure that:","Then, modify the section labeled authentication. See SAML parameters shown in example below:","Please note that you will have to modify all the above to match your own settings. saml.idp.comm.binding.type can be left empty if saml.idp.comm.binding.settings=defaultBinding. The saml.logout.* settings above reflect the settings of an IDP that supports Single Logout (hopefully the default in most cases - more details in section below).","In the case that you are running cBioPortal behind a reverse proxy that handles the SSL certificates (such as nginx or traefik), you will have to also specify saml.sp.metadata.entitybaseurl. This should point to https://host.example.come:443. This setting is required such that cBioPortal uses the Spring SAML library appropriately for creating redirects back into cBioPortal.","In addition there is a known bug where redirect from the cBioPortal instance always goes over http instead of https ( https://github.com/cBioPortal/cbioportal/issues/6342). To get around this issue you can pass the full URL including https to the webapp-runnner.jar command with e.g. --proxy-base-url https://mycbioportalinstance.org."]},{"l":"Custom scenarios","p":["ℹ️ Some settings may need to be adjusted to non-default values, depending on your IDP. For example, if your IDP required HTTP-GET requests instead of HTTP-POST, you need to set these properties as such:","If you need a very different parsing of the SAML tokens than what is done at org.cbioportal.security.spring.authentication.saml.SAMLUserDetailsServiceImpl, you can point the saml.custom.userservice.class to your own implementation:","⚠️ The properties saml.idp.metadata.attribute.email, and saml.idp.metadata.attribute.userName can also vary per IDP. It is important to set these correctly since these are a required field by the cBioPortal SAML parser (that is, if org.cbioportal.security.spring.authentication.saml.SAMLUserDetailsServiceImpl is chosen for property saml.custom.userservice.class).","⚠️ Some IDPs like to provide their own logout page (e.g. when they don't support the custom SAML Single Logout protocol). For this you can adjust the saml.logout.url property to a custom URL provided by the IDP. Also set the saml.logout.local=true property in this case to indicate that global logout (or Single Logout) is not supported by IDP:","⚠️ Some IDPs (e.g. Azure Active Directory) cache user data for more than 2 hours causing cbioportal to complain that the authentication statement is too old to be used. You can fix this problem by setting forceAuthN to true. Below is an example how you can do this with the properties. You can choose any binding type you like. bindings:HTTP-Redirect is given just as an example."]},{"l":"More customizations","p":["If your IDP does not have the flexibility of sending the specific credential fields expected by our default \"user details parsers\" implementation (i.e. security/security-spring/src/main/java/org/cbioportal/security/spring/authentication/saml/SAMLUserDetailsServiceImpl.java expects field mail to be present in the SAML credential), then please let us know via a new issue at our issue tracking system, so we can evaluate whether this is a scenario we would like to support in the default code. You can also consider adding your own version of the SAMLUserDetailsService class."]},{"l":"Authorizing Users","p":["Next, please read the Wiki page on User Authorization, and add user rights for a single user."]},{"i":"configuring-the-loginjsp-page-not-applicable-to-most-external-idps","l":"Configuring the Login.jsp Page (not applicable to most external IDPs)","p":["The login page is configurable via the portal.properties properties skin.authorization_message and skin.login.saml.registration_htm. For example in skin.authorization_message you can be set to something like this:","and skin.login.saml.registration_htm can be set to:","You can also set a standard text in skin.login.contact_html that will appear in case of problems:"]},{"l":"Doing a Test Run","p":["You are now ready to go.","Rebuild the WAR file and follow the Deployment with authentication steps using authenticate=saml.","Then, go to: http://localhost:8080/.","If all goes well, the following should happen:","You will be redirected to the OneLogin Login Page.","After authenticating, you will be redirected back to your local instance of cBioPortal.","If this does not happen, see the Troubleshooting Tips below."]},{"l":"Troubleshooting Tips"},{"l":"Logging","p":["Getting this to work requires many steps, and can be a bit tricky. If you get stuck or get an obscure error message, your best bet is to turn on all DEBUG logging. This can be done via src/main/resources/logback.xml. For example:","Then, rebuild the WAR, redeploy, and try to authenticate again. Your log file will then include hundreds of SAML-specific messages, even the full XML of each SAML message, and this should help you debug the error."]},{"l":"Seeing the SAML messages","p":["Another tool we can use to troubleshoot is SAML tracer ( https://addons.mozilla.org/en-US/firefox/addon/saml-tracer/). You can add this to Firefox and it will give you an extra menu item in \"Tools\". Go through the loging steps and you will see the SAML messages that are sent by the IDP."]},{"l":"Obtaining the Service Provider Meta Data File","p":["By default, the portal will automatically generate a Service Provider (SP) Meta Data File. You may need to provide this file to your Identity Provider (IP).","You can access the Service Provider Meta Data File via a URL such as:","http://localhost:8080/saml/metadata"]}],[{"l":"Authenticating Users via LDAP","p":["To connect cBioPortal to an external user database such as Active Directory will require the installation of Keycloak. Please read the Wiki page on Authenticating and Authorizing Users via Keycloak for information on how to connect the cBioPortal with Keycloak. You can also read how to connected Keycloak to Active Directory via LDAP on the User Storage Federation webpage of the Keycloak website."]}],[{"l":"Authenticating and Authorizing Users via Keycloak","p":["⚠️ This documentation is for keycloak