Generalized Application of Co-Occurrence Matrices and Haralick Texture R package gtexture version 1.0.1 Generalizes application of gray-level co-occurrence matrix (GLCM) metrics to objects outside of images. The current focus is to apply GLCM metrics to the study of biological networks and fitness landscapes that are used in studying evolutionary medicine and biology, particularly the evolution of cancer resistance. The package was developed as part of the author's publication in Physics in Medicine and Biology Barker-Clarke et al. (2023) <doi:10.1088/1361-6560/ace305>. A general reference to learn more about mathematical oncology can be found at Rockne et al. (2019) <doi:10.1088/1478-3975/ab1a09>. Software Imports: dlookr, dplyr (>= 1.0), fitscape (>= 0.1), igraph, magrittr (>= 2.0), rlang, tidyr Suggests: stats, testthat Rowan Barker-Clarke <rowanbarkerclarke@gmail.com> Comprehensive R Archive Network (CRAN) Rowan Barker-Clarke [aut, cre] (ORCID: <https://orcid.org/0000-0003-1961-7919>), Raoul Wadhwa [aut] (ORCID: <https://orcid.org/0000-0003-0503-9580>), Davis Weaver [aut], Jacob Scott [aut] (ORCID: <https://orcid.org/0000-0003-2971-7673>) MIT + file LICENSE (https://CRAN.R-project.org/package=gtexture/LICENSE) 2025-09-02 application/tgz https://CRAN.R-project.org/package=gtexture doi:10.32614/CRAN.package.gtexture