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HTGM4D  

Four Dimensional High Throughput 'GoMiner'
View on CRAN: Click here


Download and install HTGM4D package within the R console
Install from CRAN:
install.packages("HTGM4D")

Install from Github:
library("remotes")
install_github("cran/HTGM4D")

Install by package version:
library("remotes")
install_version("HTGM4D", "1.0")



Attach the package and use:
library("HTGM4D")
Maintained by
Barry Zeeberg
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-05-02
Latest Update: 2026-05-02
Description:
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.
How to cite:
Barry Zeeberg (2026). HTGM4D: Four Dimensional High Throughput 'GoMiner'. R package version 1.0, https://cran.r-project.org/web/packages/HTGM4D. Accessed 29 Jul. 2026.
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Complete documentation for HTGM4D
Functions, R codes and Examples using the HTGM4D R package
Full HTGM4D package functions and examples
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