Please use this identifier to cite or link to this item: doi:10.22028/D291-47841
Title: DicePlot: a package for high-dimensional categorical data visualization
Author(s): Flotho, Matthias
Flotho, Philipp
Keller, Andreas
Language: English
Title: Bioinformatics
Volume: 42 (2026)
Issue: 2
Publisher/Platform: Oxford University Press
Year of Publication: 2025
DDC notations: 610 Medicine and health
Publikation type: Journal Article
Abstract: Summary Visualization of multidimensional, categorical data is a common challenge across scientific domains and, in particular, the life sciences. The goal is to create a comprehensive overview of the underlying data which enables one to assess multiple variables. One application where such visualizations are particularly useful is gene or pathway analysis, which involves checking for dysregulation in known biological mechanisms and functions across multiple conditions. Here, we propose a new visualization approach that encodes such data in an intuitive representation: DicePlots visualize up to four distinct categorical classes in a single view using elements resembling dice faces, whereas DominoPlots add an additional layer of information for binary comparison. Availability and implementation The code is available as the diceplot R package and the pydiceplot on PyPI. All source code is available at https://github.com/maflot. Contact The repo is managed actively and we encourage community contributions and requests.
DOI of the first publication: 10.1093/bioinformatics/btaf337
URL of the first publication: https://doi.org/10.1093/bioinformatics/btaf337
Link to this record: urn:nbn:de:bsz:291--ds-478410
hdl:20.500.11880/41839
http://dx.doi.org/10.22028/D291-47841
ISSN: 1367-4811
Date of registration: 15-May-2026
Faculty: M - Medizinische Fakultät
Department: M - Medizinische Biometrie, Epidemiologie und medizinische Informatik
Professorship: M - Univ.-Prof. Dr. Andreas Keller
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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