GO trimming : systematically reducing redundancy in large Gene Ontology datasets

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dc.contributor.authorJantzen, Stuart G.
dc.contributor.authorSutherland, Ben J.G.
dc.contributor.authorMinkley, David R.
dc.contributor.authorKoop, Benjamin F.
dc.date.accessioned2014-01-07T23:30:16Z
dc.date.available2014-01-07T23:30:16Z
dc.date.copyright2011en_US
dc.date.issued2011-07-28
dc.descriptionBioMed Centralen_US
dc.description.abstractBackground: The increased accessibility of gene expression tools has enabled a wide variety of experiments utilizing transcriptomic analyses. As these tools increase in prevalence, the need for improved standardization in processing and presentation of data increases, as does the need to guard against interpretation bias. Gene Ontology (GO) analysis is a powerful method of interpreting and summarizing biological functions. However, while there are many tools available to investigate GO enrichment, there remains a need for methods that directly remove redundant terms from enriched GO lists that often provide little, if any, additional information. Findings: Here we present a simple yet novel method called GO Trimming that utilizes an algorithm designed to reduce redundancy in lists of enriched GO categories. Depending on the needs of the user, this method can be performed with variable stringency. In the example presented here, an initial list of 90 terms was reduced to 54, eliminating 36 largely redundant terms. We also compare this method to existing methods and find that GO Trimming, while simple, performs well to eliminate redundant terms in a large dataset throughout the depth of the GO hierarchy. Conclusions: The GO Trimming method provides an alternative to other procedures, some of which involve removing large numbers of terms prior to enrichment analysis. This method should free up the researcher from analyzing overly large, redundant lists, and instead enable the concise presentation of manageable, informative GO lists. The implementation of this tool is freely available at: http://lucy.ceh.uvic.ca/go_trimming/cbr_go_trimming.pyen_US
dc.description.reviewstatusRevieweden_US
dc.description.scholarlevelFacultyen_US
dc.identifier.citationJantzen et al.: GO Trimming: Systematically reducing redundancy in large Gene Ontology datasets. BMC Research Notes 2011 4:267.en_US
dc.identifier.urihttp://www.biomedcentral.com/1756-0500/4/267
dc.identifier.urihttp://dx.doi.org/10.1186/1756-0500-4-267
dc.identifier.urihttp://hdl.handle.net/1828/5145
dc.language.isoenen_US
dc.publisherBioMed Centralen_US
dc.subjectCentre for Biomedical Research
dc.subject.departmentDepartment of Biology
dc.titleGO trimming : systematically reducing redundancy in large Gene Ontology datasetsen_US
dc.typeArticleen_US

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