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dc.contributor.author Supek, Fran
dc.contributor.author Škunca, Nieves
dc.date.accessioned 2017-05-08T08:38:04Z
dc.date.available 2017-05-08T08:38:04Z
dc.date.issued 2017
dc.identifier.citation Supek F, Škunca N. Visualizing GO Annotations. Methods in Molecular Biology. 2017;1446:207-20. DOI: 10.1007/978-1-4939-3743-1_15
dc.identifier.issn 1064-3745
dc.identifier.uri http://hdl.handle.net/10230/32105
dc.description.abstract 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.
dc.description.sponsorship We acknowledge the support of the European Commission via grants MAESTRA (ICT-2013-612944) and InnoMol (FP7-REGPOT-2012-2013-1-316289), and of the Croatian Science Foundation grant MultiCaST (# 5660). Open Access charges were funded by the University College London Library, the Swiss Institute of Bioinformatics, the Agassiz Foundation, and the Foundation for the University of Lausanne.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Springer
dc.relation.ispartof Methods in Molecular Biology. 2017;1446:207-20
dc.rights © Springer The final publication is available at Springer via http://dx.doi.org/10.1007/978-1-4939-3743-1_15.
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.title Visualizing GO Annotations
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1007/978-1-4939-3743-1_15
dc.subject.keyword Gene Ontology
dc.subject.keyword Visualization
dc.subject.keyword Interpretation
dc.subject.keyword Redundancy
dc.subject.keyword Enrichment
dc.subject.keyword Tools
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/612944
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/316289
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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