ArticleIEEE transactions on visualization and computer graphics2025
Understanding Visualization Authoring Techniques for Genomics Data in the Context of Personas and Tasks.
Article in IEEE transactions on visualization and computer graphics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Geranium: Multimodal Retrieval of Genomics Data Visualizations.IEEE transactions on visualization and computer graphics · 2026Article
- Uchimata: a toolkit for visualization of 3D genome structures on the web and in computational notebooks.Bioinformatics (Oxford, England) · 2026Article
- Design Space and Declarative Grammar for 3D Genomic Data Visualization.IEEE transactions on visualization and computer graphics · 2026Article
- Gosling Designer: a Platform to Democratize Construction and Sharing of Genomics Data Visualization Tools.ArXiv · 2025Article
- Safire: Similarity Framework for Visualization Retrieval.IEEE Visualization Conference : VIS. IEEE Conference on Visualization · 2025Article
- Uchimata: a toolkit for visualization of 3D genome structures on the web and in computational notebooks.ArXiv · 2025Article
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Genomics experts rely on visualization to extract and share insights from complex and large-scale datasets. Beyond off-the-shelf tools for data exploration, there is an increasing need for platforms that aid experts in authoring customized visualizations for both exploration and communication of insights. A variety of interactive techniques have been proposed for authoring data visualizations, such as template editing, shelf configuration, natural language input, and code editors. However, it remains unclear how genomics experts create visualizations and which techniques best support their visualization tasks and needs. To address this gap, we conducted two user studies with genomics researchers: (1) semi-structured interviews (n=20) to identify the tasks, user contexts, and current visualization authoring techniques and (2) an exploratory study (n=13) using visual probes to elicit users' intents and desired techniques when creating visualizations. Our contributions include (1) a characterization of how visualization authoring is currently utilized in genomics visualization, identifying limitations and benefits in light of common criteria for authoring tools, and (2) generalizable design implications for genomics visualization authoring tools based on our findings on task- and user-specific usefulness of authoring techniques. All supplemental materials are available at https://osf.io/bdj4v/.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.