Genomic Data Commons

The Genomic Data Commons (GDC) is a cancer knowledge network that supports hosting, standardization, and analysis of genomic, clinical, and biospecimen data from cancer research programs. The GDC harmonizes raw sequencing data, identifies and applies state-of-the-art bioinformatics methods for generating mutation calls, structural variants and other high-level data, and provides scalable downloads and web-based analysis tools. 

Data in the GDC are structured using the GDC Data Model, with properties and data types defined in the GDC Data Dictionary. The data model is continually updated to accommodate evolving genomic technology and biomedical research, with guidance and input from the research community and external reference standards.

Because of the personal nature of genomic data, some genomic data in the GDC may be controlled access, requiring eRA Commons authentication and dbGaP authorization to access the data. Whether a dataset is open or controlled is determined according to Data Access Policies in a process driven by informed consent of research participants. 

Data in the GDC are accessible through many ways, including: the GDC Data Portal, a web-based platform with a graphical user interface to search for and download data; the GDC Data Transfer Tool (DTT), a client-based utility to efficiently download and upload large volumes of data; and the GDC Application Programming Interface (API), a programmatic interface to query, download, upload, and analyze data.

In addition to providing access to data, the GDC provides several analysis tools via the Data Portal Exploration and Analysis features:

• Mutation Frequency Distribution Graph - View the most frequently mutated genes for any cohort and plot frequencies of cases with mutations and copy number variants for a selected gene
• OncoGrid - Visualize combinations of gene mutations and copy number variants for a project or custom cohort
• Survival Analysis - Compare overall survival of any two cohorts, such as patients with and without a mutated gene of interest
• Set Operations - Perform operations on gene, mutation, or case sets by visualizing set similarities and differences in a Venn diagram
• Cohort Comparison - Display the survival analysis of custom case sets and compare characteristics such as gender, vital status and age at diagnosis
• Clinical Data Analysis - Select a clinical variable and view cohort-level survival plots, histograms, box plots, and Q-Q plots
• Protein Viewer - Visualize gene mutations mapped to their protein functional domains