Nucleic Acids Research Advance Access originally published online on January 10, 2008
Nucleic Acids Research 2008 36(2):e12; doi:10.1093/nar/gkm1167
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Nucleic Acids Research, 2008, Vol. 36, No. 2 e12
© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Gene Ontology annotation quality analysis in model eukaryotes
1Department of Basic Sciences, 2Department of Computer Science and Engineering, 3Institute of Digital Biology, 4Mississippi Agricultural and Forestry Experiment Station and 5Life Sciences and Biotechnology Institute, Mississippi State University, Mississippi 39762, USA
*To whom correspondence should be addressed. Tel: +1 662 325 5859; Fax: +1 662 325 1031; Email: fmccarthy{at}cvm.msstate.edu
Received September 4, 2007. Revised November 30, 2007. Accepted December 18, 2007.
Functional analysis using the Gene Ontology (GO) is crucial for array analysis, but it is often difficult for researchers to assess the amount and quality of GO annotations associated with different sets of gene products. In many cases the source of the GO annotations and the date the GO annotations were last updated is not apparent, further complicating a researchers’ ability to assess the quality of the GO data provided. Moreover, GO biocurators need to ensure that the GO quality is maintained and optimal for the functional processes that are most relevant for their research community. We report the GO Annotation Quality (GAQ) score, a quantitative measure of GO quality that includes breadth of GO annotation, the level of detail of annotation and the type of evidence used to make the annotation. As a case study, we apply the GAQ scoring method to a set of diverse eukaryotes and demonstrate how the GAQ score can be used to track changes in GO annotations over time and to assess the quality of GO annotations available for specific biological processes. The GAQ score also allows researchers to quantitatively assess the functional data available for their experimental systems (arrays or databases).
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.
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