Building Sets of Variables in a Probabilistic Framework R package setweaver version 1.0.0 Create sets of variables based on a mutual information approach. In this context, a set is a collection of distinct elements (e.g., variables) that can also be treated as a single entity. Mutual information, a concept from probability theory, quantifies the dependence between two variables by expressing how much information about one variable can be gained from observing the other. Furthermore, you can analyze, and visualize these sets in order to better understand the relationships among variables. Software Depends: R (>= 4.1.0) Imports: dplyr (>= 1.1.4), igraph (>= 2.1.2), permutes (>= 2.8), pheatmap (>= 1.0.13), splitTools (>= 1.0.1) Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Nicolas Leenaerts <nicolas.leenaerts@kuleuven.be> Comprehensive R Archive Network (CRAN) Nicolas Leenaerts [aut, cre, cph] (ORCID: <https://orcid.org/0000-0003-2421-6845>), Aaron Fisher [aut, cph] (ORCID: <https://orcid.org/0000-0001-9754-4618>) CC BY 4.0 2026-02-04 application/tgz https://CRAN.R-project.org/package=setweaver doi:10.32614/CRAN.package.setweaver