cBioPortal for Cancer Genomics

Big Data Open Source

cBioPortal for Cancer Genomics is one of the most widely used platforms for visualizing and analyzing cancer genomics data. The platform is fully open source and actively maintained by KSG @ Dana-Farber Cancer Institute, Memorial Sloan Kettering Cancer Center, Princess Margaret Cancer Centre, and The Hyve. KSG also maintains a local instance — cBioPortal @ DFCI — enabling researchers to explore all genomic data generated by the Profile project.

Key Capabilities

OncoPrint

Visual summary of genomic alterations across a cohort of patients — mutations, copy number changes, and fusions in a single view.

Mutation Analysis

Explore somatic mutations across genes and cancer types, with lollipop plots and protein domain annotations.

Survival Analysis

Kaplan-Meier survival curves stratified by genomic alterations, expression levels, or clinical attributes.

Gene Expression

Compare mRNA expression across cancer types, patient cohorts, and genomic subgroups.

Multi-Study Analysis

Query and compare data across hundreds of published cancer studies simultaneously.

Clinical Integration

Correlate genomic findings with clinical data including tumor type, treatment history, and outcomes.

Screenshots

OncoPrint view — Lung Adenocarcinoma

OncoPrint — genomic alteration summary across a lung adenocarcinoma cohort

Mutation Mapper — EGFR protein

Mutation Mapper — EGFR somatic mutations mapped to protein domains

MSK-CHORD Study View

Study view — MSK-CHORD (24,950 patients, MSK-IMPACT). Click to enlarge.

cBioPortal Patient View

Patient view — clinical timeline and genomic summary for an individual patient. Click to enlarge.

cBioPortal @ DFCI

In addition to the public platform, KSG maintains a local instance of cBioPortal at Dana-Farber. This private instance gives DFCI researchers secure access to genomic data from the Profile project — one of the most comprehensive clinical sequencing efforts in the US — enabling them to explore patient-level data and drive research discoveries directly from clinical sequencing results.

cbioportal.org →   GitHub →