Package: HTGM2D
Version: 1.1.1
Date: 2026-02-03
Title: Two Dimensional High Throughput 'GoMiner'
Authors@R: c(
          person("Barry", "Zeeberg", email = "barryz2013@gmail.com",
                role = c("aut", "cre")))
Maintainer: Barry Zeeberg <barryz2013@gmail.com>
Author: Barry Zeeberg [aut, cre]
Depends: R (>= 4.2.0)
Imports: minimalistGODB, GoMiner, HTGM, grDevices, stats, gplots,
        jaccard, vprint, randomGODB, HGNChelper
LazyData: true
LazyDataCompression: xz
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.
License: GPL (>= 2)
Encoding: UTF-8
VignetteBuilder: knitr
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
RoxygenNote: 7.3.3
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2026-06-20 09:17:51 UTC; root
Config/pak/sysreqs: cmake make libicu-dev libuv1-dev zlib1g-dev
Repository: https://barryzee.r-universe.dev
Date/Publication: 2026-02-03 23:00:32 UTC
RemoteUrl: https://github.com/cran/HTGM2D
RemoteRef: HEAD
RemoteSha: 860e4a7b390e81039f2b10b3a1595858d4764e9a