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Nils Gehlenborg (EMBL-EBI, Cambridge, United Kingdom)Heat maps are commonly used to visualize gene expression data, however, they have severe shortcomings for data sets with hundreds of samples. We have developed the glyph-based Space Maps visualization technique, which is conceptually similar to Value and Relation Displays. The technique comprises two steps: Generation of glyphs to represent gene expression profiles and 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. We have applied the Space Maps technique expression profiles from a meta data set with 5,372 samples. The arrangement of the glyphs represents an overview of the global patterns in the data, such as clusters and outliers. Furthermore, the visualization provides insight into local patterns in the gene expression profiles. We were able to explain several of the clusters and outliers and assign meaningful labels to them.