GeRnika: An R Package for the Simulation, Visualization and Comparison of Tumor Phylogenies

The development of methods to study intratumoral heterogeneity and tumor phylogenies is a highly active area of research. However, the advancement of these approaches often necessitates access to substantial amounts of data, which can be challenging and expensive to acquire. Moreover, the assessment of results requires tools for visualizing and comparing tumor phylogenies. In this paper, we introduce GeRnika, an R package designed to address these needs by enabling the simulation, visualization, and comparison of tumor evolution data. In summary, GeRnika provides researchers with a user-friendly tool that facilitates the analysis of their approaches aimed at studying tumor composition and evolutionary history.

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Publication Details

Journal
The R Journal
Published
2026-02-11
DOI
https://doi.org/10.32614/rj-2025-042
Primary Topic
Mathematical Biology Tumor Growth
Type
article
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article

GeRnika: An R Package for the Simulation, Visualization and Comparison of Tumor Phylogenies

Maitena Tellaetxe-Abete, Aitor Sánchez-Ferrera, Borja Calvo-Molinos
The R Journal
Mathematical Biology Tumor Growth
article

GeRnika: An R Package for the Simulation, Visualization and Comparison of Tumor Phylogenies

Maitena Tellaetxe-Abete, Aitor Sánchez-Ferrera, Borja Calvo-Molinos
article en

Abstract

The development of methods to study intratumoral heterogeneity and tumor phylogenies is a highly active area of research. However, the advancement of these approaches often necessitates access to substantial amounts of data, which can be challenging and expensive to acquire. Moreover, the assessment of results requires tools for visualizing and comparing tumor phylogenies. In this paper, we introduce GeRnika, an R package designed to address these needs by enabling the simulation, visualization, and comparison of tumor evolution data. In summary, GeRnika provides researchers with a user-friendly tool that facilitates the analysis of their approaches aimed at studying tumor composition and evolutionary history.

The R JournalVol. 17(4)
Intelligent Systems Research (United States) (US)
Zero hunger
Openalex Percentile: Top 32%
Mathematical Biology Tumor Growth
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