Summary: Phylogenetic trees with hundreds of thousands of leaves are now being inferred from sequence data, posing significant challenges for visualization and exploratory analysis. Image data supplying valuable context for species in trees (and cues for exploring them) are becoming increasingly available in biodiversity databases and elsewhere but have rarely been built into tree visualization software in a scalable way. Ceiba lets the user explore large trees and inspect image collection arrays (sets of 'homologous' images) comprising mixtures of 2D and 3D image objects. Ceiba exploits recent improvements in graphics hardware, OpenGL toolkits and many standard high-performance computer graphics strategies, such as texture compression, level of detail control, culling, animations and image caching. Its tree layouts can be tuned by user-provided phylogenetic definitions of subtrees. The code has been extensively tested on phylogenies of up to 55 000 leaves and images.
ASJC Scopus subject areas
- Statistics and Probability
- Molecular Biology
- Computer Science Applications
- Computational Theory and Mathematics
- Computational Mathematics