Improved Histogram Binning in the cBioPortal Study View

At The Hyve, we implemented improvements to the histograms displayed on cBioPortal's Study View page. The added feature allows users to generate custom bins based on the data's quartiles or median or by defining the bin size.

Previously, if a user wanted to define custom bins, they needed to write out all the boundaries of the bins - a rather tedious and error-prone approach. The histogram feature developed by The Hyve makes this process much easier and more robust. It has been included in cBioPortal version 4.1.9.


cBioPortal is widely known as a user-friendly tool for visualizing and analyzing cancer genomics data. One of cBioPortal's many popular features is the Study view page. This page summarizes all the clinical and genomic data available in a study by visually representing them in histograms, pie charts, and tables.

cBioPortal's Study view or Study Summary page is interactive, and users can select a subset of patients by selecting columns of histograms they are interested in. Users can also create smaller patient groups from histograms and view details of the subset in the Group Comparison view.

What is new?

Instead of the old pop-up window that allowed users to define custom bins by listing all the bin boundaries, there is now a new pop-up window that provides various more convenient options to define the bins while at the same time supporting the old method.

The old method only allowed Users to specify the bin boundaries of the x-axis. In the new method, users can create custom bins in three new ways:

  1. Based on the Quartiles of the data
  2. By splitting the data along the median
  3. By generating bins based on "Bin Size" and "Minimum Value." A bin is a single range of continuous values used to group values in a chart.
cBioPortal's Custom Bins for Histograms. The old method (left) allows users to list all the values, whereas the new method (right) has multiple methods to generate bins.

Try it yourself

1. Visit and, for example, look at the Brain Lower Grade Glioma (TCGA, PanCancer Atlas) study. Select the study and click on the "Explore Selected Study" button. This will lead you to the Study View page.

2. The Study View page summarizes all the clinical and genomic information available in this study.

cBioPortal's Study View page outlines all the genomic and clinical data available for the selected study.

3. Look at the "Diagnosis Age" histogram in more detail. When you select the burger icon on the Diagnosis Age histogram, a menu with some options appears.

Histogram showing the Diagnosis age of patients.

4. To define custom bins, click "Custom Bins." The following dialog box will appear:

Custom Bins dialog box.

A few options are listed here. You can generate bins based on the Quartiles or Median Split. Another option is to click on the "Generate bins" option and fill in the Bin size and Minimum value.
You can also select the "Custom Bins" radio button and specify bin boundaries of the x-axis by listing them out.
For this example, let's update the Bin size to 10, so the histogram will now group the diagnosis age in groups of 10, starting from the age of 15, as shown below:

Diagnosis Age histogram updated with custom bins.

The new bin boundaries will also be updated in the "Custom Bins" text box. Here you can fine-tune the values if you like.

Quick selection

This is an example of how to use the "Custom bins" option in cBioPortal. Creating custom bins will allow users to more quickly and easily select patients of interest, examine outliers, and create unique filters to subset samples of interest.

The Hyve's team provides services to develop, extend and improve features in cBioPortal, such as the one described in this article. Implemented features are released to the community via the cBioPortal repository on GitHub. We hope you like this new feature and that it proves helpful in your work. For inquiries on cBioPortal feature developments or other services our team provides around cBioPortal, feel free to contact us.

Written by

Jessica Singh