Visualizing GO Annotations.
Contemporary techniques in biology produce readouts for large numbers of genes simultaneously, the typical example being differential gene expression measurements. Moreover, those genes are often richly annotated using GO terms that describe gene function and that can be used to summarize the results of the genome-scale experiments. However, making sense of such GO enrichment analyses may be challenging. For instance, overrepresented GO functions in a set of differentially expressed genes are typically output as a flat list, a format not adequate to capture the complexities of the hierarchical structure of the GO annotation labels.In this chapter, we survey various methods to visualize large, difficult-to-interpret lists of GO terms. We catalog their availability-Web-based or standalone, the main principles they employ in summarizing large lists of GO terms, and the visualization styles they support. These brief commentaries on each software are intended as a helpful inventory, rather than comprehensive descriptions of the underlying algorithms. Instead, we show examples of their use and suggest that the choice of an appropriate visualization tool may be crucial to the utility of GO in biological discovery.
Division of Electronics, Ruder Boskovic Institute, 10000, Zagreb, Croatia. fran.supek@irb.hr.|EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, 08003, Barcelona, Spain. fran.supek@irb.hr.|Universitat Pompeu Fabra (UPF), 08003, Barcelona, Spain. fran.supek@irb.hr.
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Supek
Department of Computer Science, ETH Zurich, Zurich, Switzerland.|SIB Swiss Institute of Bioinformatics, Zurich, Switzerland.|University College London, London, UK.
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D000818:Animals; D001296:Audiovisual Aids; D030541:Databases, Genetic; D020869:Gene Expression Profiling; D063990:Gene Ontology; D006801:Humans; D020407:Internet; D012984:Software
Enrichment; Gene Ontology; Interpretation; Redundancy; Tools; Visualization