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HTGM2D
View on CRAN: Click
here
Download and install HTGM2D package within the R console
Install from CRAN:
install.packages("HTGM2D")
Install from Github:
library("remotes")
install_github("cran/HTGM2D") Install by package version:
library("remotes")
install_version("HTGM2D", "1.1.1") Attach the package and use:
library("HTGM2D")
Maintained by
Barry Zeeberg
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First Published: 2025-04-07
Latest Update: 2025-05-18
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 developed a two-dimensional version of 'High-Throughput GoMiner' ('HTGM2D'). I generate a 2D heat map whose axes are any two of BP, MF, or CC, and the value within a picture element of the heat map reflects the Jaccard metric p-value for the number of genes in common for the corresponding pair.
How to cite:
Barry Zeeberg (2025). HTGM2D: Two Dimensional High Throughput 'GoMiner'. R package version 1.1.1, https://cran.r-project.org/web/packages/HTGM2D. Accessed 03 Oct. 2026.
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