cBioPortal Updates Offer Joint Analysis of Genetic and Clinical Data
If you’re struggling to combine genetic data with clinical findings, you’ll want to know about the latest enhancements to cBioPortal, an interface that helps you work with large-scale cancer genomic data sets like The Cancer Genome Atlas (TCGA).
Researchers began building cBioPortal over a decade ago to help visualize and analyze data from TCGA. In recent years, the developers upgraded the platform to support data from the American Association for Cancer Research’s Project GENIE (i.e., the Genomics Evidence Neoplasia Information Exchange). Project GENIE features genetic data from more than 130,000 patients. The project now also includes clinical data and treatment information from thousands of those patients (as part of the long-term GENIE Biopharma Collaborative [BPC] study).
Now, with the latest updates to cBioPortal, you can seamlessly analyze genetic and clinical data together to better understand cancer and how it progresses over time.
You can view genetic and clinical data in four different ways:
- “Study View” lets you explore both genetic and clinical data in a data set.
- “Query/Results View” allows you to analyze and visualize alterations in specific genes.
- “Comparison View” enables you to select and compare genetic and clinical features from two or more groups.
- “Patient View” lets you visualize and interpret a patient’s genetic and clinical data.
As noted by corresponding author, Mr. Ino de Bruijn, “Even within a single institution, it can be a Herculean task to combine clinical data with genetic sequencing data, as they are often stored across multiple databases and in very different formats.” He added, “These new cBioPortal software enhancements, together with the public GENIE BPC data set, enable you to explore complex clinical and genetic
Mr. Bruijn and his coauthors say they’re planning additional upgrades to cBioPortal, including adding new ways to query samples from a specific time frame (not just before and after a particular treatment). The researchers also are working on a solution that will help you build a cohort of patients given consecutive treatments, rather than a single, one-time therapy.