Det. (Distance Encoded Tree): A Scalable Visualization Tool for Mapping Multiple Traits to Large Evolutionary Trees

Evolutionary biologists are often interested in finding correlations among biological traits (or attributes) across a number of species, as such correlations may lead to testable hypotheses about the underlying function. Because some species are more closely related than others, computing and visualizing these correlations must be done in the context of the evolutionary tree that relates the species. Although dozens of visualizations for correlated traits have been developed over the decades, the recent explosive growth in the number of traits and species has created a need for a visualization that can scale to dozens of traits mapped to thousands of species and their evolutionary tree to allow the interactive exploration of complex interactions. In this paper, we introduce Det., called detective, an evolutionary tree visualization that allows biologists to see multiple attributes of leaf nodes. We describe a new tree layout algorithm to represent different branch lengths and several visualization and intereaction techniques to address user requirements. We also report informal feedbacks we collected from evolutionary biologists.