Presentation at SICB+ 2022. Acacia Ackles and Emily Dolson.
Live Demo: [ Ссылка ]
Project Repository: [ Ссылка ]
Twitter: @alackles
Github: @alackles
Website: [ Ссылка ]
ABSTRACT
Data visualization is a key part of both scientific communication and scientific discovery. Good data visualizations can go beyond simply providing a graphical representation of our data, and can actually lead to new connections and intuitions. Poor visualizations can do the exact opposite, by leading us astray via imperfect information. One area of evolutionary biology where the efficacy of data visualization is particularly relevant is in Sewall Wright's fitness landscapes. Typically, such landscapes are visualized as two-dimensional phenotype space mapped onto a third fitness dimension. However, this limits the data that can be visualized to only two variables; in cases where landscapes have three or more dimensions, this dimensional reduction may be unintuitive or even misleading about the true structure of the fitness landscape. Fortunately, the possibilities for multi-dimensional visualization are growing with the rise of virtual reality (VR) headsets and software. Here we use such VR software in combination with web-enabled data tools such as D3 and A-frame to create three dimensional phenotype landscapes with fitness as a fourth dimension. We are able to map fitness trajectories across 3D space and create visualizations which can be viewed in any VR headset or in any web browser. We hope that by leveraging the new opportunities provided by VR and similar software, researchers can continue to expand our intuition into new dimensions.
