Four Dimensional High Throughput 'GoMiner' R package HTGM4D version 1.0 The Gene Ontology (GO) Consortium <https://geneontology.org/> organizes genes into hierarchical categories based on biological process (BP), molecular function (MF) and cellular component (CC, i.e., subcellular localization). Tools such as 'GoMiner' (see Zeeberg, B.R., Feng, W., Wang, G. et al. (2003) <doi:10.1186/gb-2003-4-4-r28>) can leverage GO to perform ontological analysis of microarray and proteomics studies, typically generating a list of significant functional categories. Microarray studies are usually analyzed with BP, whereas proteomics researchers often prefer CC. To capture the benefit of both of those ontologies, I now present an enhancement of the existing two-dimensional version of 'High-Throughput GoMiner' ('HTGM2D'), which is called 'HTGM4D'. The original 'HTGM2D' is augmented by adding two instances of the original 'GoMiner' genes versus categories heatmaps, aligned with the categories axes of the 'HTGM2D' heatmap. Software Depends: R (>= 4.2.0) Imports: minimalistGODB, GoMiner, HTGM, HTGM2D, grDevices, stats, gplots, vprint, randomGODB, HGNChelper, png, magick, svglite, utils, graphics Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Barry Zeeberg <barryz2013@gmail.com> Comprehensive R Archive Network (CRAN) Barry Zeeberg [aut, cre] GPL (>= 2) 2026-05-02 application/tgz https://CRAN.R-project.org/package=HTGM4D doi:10.32614/CRAN.package.HTGM4D