High-dimensional data are often visualized by dimensionality reduction methods whose goals are not directly related to visualization. We use a recent formalization of visualization as information retrieval and apply that formalism to data with structured annotations: we analyze gene expression data with annotations from the Gene Ontology (GO). We show that using the GO information in visualization yields better retrieval with respect to known ontological relationships and allows discovery of data properties not explained by the ontology.

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JP, HA, and SK belong to HIIT and AIRC. Authors were supported by PASCAL2, an EMBL fellowship, and Academy of Finland decision 123983.