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.

Barry Zeeberg

x_l: HTGM2D data set

Description

Usage

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