Biowheel rapidly displays any tabular data in a circular heatmap, where columns are represented as rings, rows as spokes, and values as colors. The video at the top of this page illustrates examples of visualizing high-dimensional molecular time-course data from the HPN-DREAM Breast Cancer challenge.

Leveraging its interactive capabilities, Biowheel facilitates data vetting and pattern discovery. Data values are displayed in real-time via tooltips when users mouse over any data-associated graphical element, offering an additional layer of information. With a simple click on a ring’s name, Biowheel will automatically sort (or unsort) samples based on values of the corresponding variable and will reorder spokes instantaneously. This interactive sorting enables fast visual comparison and pattern discovery.

Fully harnessing the pattern recognition power in human eyes, Biowheel integrates its interactive visualization platform with a semi-supervised clustering algorithm (MPCK-Means) to enable visually guided clustering. Clustering solutions are iteratively refined based on user-defined and visually inspired cluster constraints in the form of must-links and cannot-links between sample pairs.