Explore. Analyze. Learn.

Welcome to Oncoscape.

A data visualization platform that empowers researchers to discover novel patterns and relationships between clinical and molecular data. Through a suite of interoperable tools, Oncoscape offers a unique and intuitive approach to hypothesis refinement.

Iterative Analysis

Seamlessly transfer knowledge among analytical tools. Discover new patterns and relationships by connecting diverse questions and answers.

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Cohort Discovery

Easily define patient sets of interest. Build, refine, and scale cohorts based on clinical and/or molecular factors.

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Interactive Visualizations

Access data and methods through a suite of visual tools. Combine the power of analysis and discovery through the simple click of a mouse.

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Interdisciplinary Science


Interested in tumor progression and molecular functions for an individual patient or patients within a scalable population.


Interested in developing, comparing, or validating models of response for given diseases.


Interested in determining the best clinical treatment for a patient given their demographic and tumor molecular profile.

Available Tools


Oncoscape hosts level 3 public TCGA datasets representing gene and patient data downloaded from UCSC Xena. To review this data in depth visit our data API. User planning to publish on the provided data must adhere to all publishing guideline set by the NIH. Datasets in Oncoscape are classified by disease type according to TCGA studies.


Interested in contributing new methods or visualizations? A version of Oncoscape exist for that! Please visit our development site to view upcoming features or discover areas to contribute. Oncoscape is an open source project hosted on GitHub that utlizes many other open source project such as Docker, MongoDB and Kong API.


Oncoscape is developed at the Fred Hutchinson Cancer Research Center under the auspices of the Seattle Translational Tumor Research initiative.


Use Cases

Oncoscape Cohorts

Watch how to select, transfer and save Oncoscape cohorts.

  1. Click Get Started.
  2. Choose a disease set. Example: Brain.
  3. Select a tool. Example:Markers + Patients.
  4. Once in Markers + Patients zoom in using mouse or trackpad.
  5. Using the Search box select a patient or gene or choice and hit Enter. Example: BRAF.
  6. Click "Show Edges of Selected".
  7. The edge connecting the BRAF selection and the patients will be shown.
  8. Click "Select Connected Nodes". Patients will now be highlighted.
  9. To view the demographics of this population use the cohorts dropdown menu on the left control bar.
  10. To save, click the "+" button.
  11. Name the cohort and click "Done".
  12. The BRAF cohort is now saved and can be pushed to the other tools.
  13. In the header find the Analysis Tools dropdown menu and select a new tool. Example: Survival Curves.
  14. Selection in survival can be toggled on or off.
  15. Push to Timelines.
  16. Push Cohorts will show in grey. To view the select closer zoom by using the grey "Click + Drag" bars on the side.

Get Started

The power of Oncoscape lies in the ability to create and move cohorts through the various tools.

Creating a saved cohort is easy. On the left side of all tools is the cohort panel. All functions related to cohorts are preformed here. Summaries for the various sections are below. It is important to note that as cohorts are selected and toggled between the clinical histograms, survival curves and summaries will update.

Selected Cohort: Add, edit or delete cohorts. Click the "+" to save, "x" to delete or click the down arrow to select a cohort for edits.

Clinical Histogram: Snapshot of clinical information, per cohort. The histogram will adjust with each cohort selection.Click the down arrow to view other filters.   e.g.   Age At Diagnosis, Gender, Race, Ethnicity, Vital, Tumor.

Survival Curve: Snapshot of Kaplan Meier survival curves, per cohort. For more in depth analysis push the saved cohorts to the survival tool.

Cohorts: All saved cohorts are listed in this area. Each cohort is clickable and will highlight the selections on the main window, as well as adjust any survival curves or clinical histograms that are associated. The last line will always show your current selection, which will also update in the Selected Cohort box at the top of the cohort panel.

Cohort Summary: Every cohort includes a summary of available information based on patients and samples.

Transfer Cohorts

Transfer cohorts at the click of a button.

Once cohorts have been created it is easy to move them to different tools for additional analysis. In the main header find the Analysis Tools button and select a new tool. The left cohort panel will appear in each tool. Additional help for individual tools can be found in the Available Tools section.



All genesets used in Oncoscape can be viewed at Geneset Details.

Oncoscape's data is based on a gene/patient relationship as defined: “non-silent somatic mutation (nonsense, missense, frame-shift indels, splice site mutations, stop codon readthroughs, change of start codon, inframe indels) was identified in the protein coding region of a gene, or any mutation identified in a non-coding gene”. Credit to Xena UCSC.


Frequently Asked Questions

What tools have export features?

Currently, the export feature is only available on the Spreadsheet tool. Users can push saved cohorts to the spreadsheet tool by clicking the the Analysis Tool button at the top of the screen. Once there click the Export button. An Excel file will get generated.

How is data saved for return visits?

All data for selections and cohorts will be automatically saved for a return visit assuming users are on the same computer to login. User logins that allow stored sessions from any device will be deployed in a future release.

How to contact the Oncoscape team directly?

On the homepage header, click the contact link, fill out the form and someone from the Oncoscape team will contact you shortly.