Gridded Visualization of Statistical Trees for High-Dimensional Multipartite Data in Systems Genetics
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Date
2025
Authors
Adams, Jane L.
Ball, Robyn L.
Bubier, Jason A.
Chesler, Elissa J.
Tory, Melanie
Borkin, Michelle A.
Ball, Robyn L.
Bubier, Jason A.
Chesler, Elissa J.
Tory, Melanie
Borkin, Michelle A.
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
In systems genetics and other multi-omics research, exploring high-dimensional relationships among molecular and physiological variables across individuals poses significant challenges. We present the Gridded Trees interface, a novel interactive visualization tool designed to facilitate the exploration of conditional inference trees, which are hierarchical models of relationships in these complex datasets. Traditional static tools struggle to reveal patterns in tree-structured data, but the Gridded Trees interface provides interactive, coordinated views, allowing users to navigate between overview and detail, filter data dynamically, and compare molecular-physiological relationships across subgroups. By combining filtering techniques, strip plots, Sankey diagrams, and small multiples, the Gridded Trees interface enhances exploratory data analysis and supports hypothesis generation. In our systems genetics research use case, this tool has revealed significant associations among microbial populations and addiction-related behavioral traits in genetically diverse mice. The Gridded Trees interface suggests broad potential for visualizing hierarchical and multipartite data across domains. A preprint of this paper as well as Supplemental Materials are available on OSF at https://osf.io/9emn5/.
Description
@article{10.1111:cgf.70113,
journal = {Computer Graphics Forum},
title = {{Gridded Visualization of Statistical Trees for High-Dimensional Multipartite Data in Systems Genetics}},
author = {Adams, Jane L. and Ball, Robyn L. and Bubier, Jason A. and Chesler, Elissa J. and Tory, Melanie and Borkin, Michelle A.},
year = {2025},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.70113}
}