Gridded Visualization of Statistical Trees for High‐Dimensional Multipartite Data in Systems Genetics

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/ .

Authors

Institutions

Publication Details

Journal
Computer Graphics Forum
Published
2025-05-23
DOI
https://doi.org/10.1111/cgf.70113
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Gridded Visualization of Statistical Trees for High‐Dimensional Multipartite Data in Systems Genetics

Elissa J. Chesler, Robyn L. Ball, Melanie Tory, Michelle A. Borkin et al.
Computer Graphics Forum
Data Visualization and Analytics
article

Gridded Visualization of Statistical Trees for High‐Dimensional Multipartite Data in Systems Genetics

Elissa J. Chesler, Robyn L. Ball, Melanie Tory, Michelle A. Borkin, Jane L. Adams, Jason A. Bubier
article en

Abstract

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/ .

Computer Graphics ForumVol. 44(3)
Boston University (US), Northeastern University (US), Jackson Laboratory (US), University of Southern Maine (US)
National Science Foundation, Jackson Laboratory, Flatiron Health, National Institutes of Health, National Institute on Drug Abuse
Openalex Percentile: Top 90%
Data Visualization and Analytics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.