Heat maps are commonly used to visualize gene expression data, however, they have severe shortcomings for data sets with hundreds of samples. To address these problems, we have developed the glyph-based Space Maps visualization technique, which is conceptually similar to the Value and Relation Displays developed by Yang et al..
The technique comprises two steps: (1) Generation of glyphs to represent gene expression profiles and (2) arrangement of the glyphs to reflect relationships between genes. Both steps support the integration of biological knowledge into the visualization, for instance in form of ontologies that describe hierarchical relationships among the conditions in the data. Similar to treemaps, this construction makes it possible to start out with an overview of the data and then view details on demand.
N Gehlenborg and A Brazma, “Visualization of Large Microarray Experiments with Space Maps” (Abstract), BMC Bioinformatics 10(Suppl 13):O7 (2009).