Please use this identifier to cite or link to this item:
Scopus Web of Science® Altmetric
Type: Journal article
Title: Estimating the annotation error rate of curated GO database sequence annotations
Author: Jones, C.
Brown, A.
Baumann, U.
Citation: BMC Bioinformatics, 2007; 8(170):WWW 1-WWW 9
Publisher: BioMed Central Ltd.
Issue Date: 2007
ISSN: 1471-2105
Statement of
Craig E. Jones, Alfred L. Brown and Ute Baumann
Abstract: Background Annotations that describe the function of sequences are enormously important to researchers during laboratory investigations and when making computational inferences. However, there has been little investigation into the data quality of sequence function annotations. Here we have developed a new method of estimating the error rate of curated sequence annotations, and applied this to the Gene Ontology (GO) sequence database (GOSeqLite). This method involved artificially adding errors to sequence annotations at known rates, and used regression to model the impact on the precision of annotations based on BLAST matched sequences. Results We estimated the error rate of curated GO sequence annotations in the GOSeqLite database (March 2006) at between 28% and 30%. Annotations made without use of sequence similarity based methods (non-ISS) had an estimated error rate of between 13% and 18%. Annotations made with the use of sequence similarity methodology (ISS) had an estimated error rate of 49%. Conclusion While the overall error rate is reasonably low, it would be prudent to treat all ISS annotations with caution. Electronic annotators that use ISS annotations as the basis of predictions are likely to have higher false prediction rates, and for this reason designers of these systems should consider avoiding ISS annotations where possible. Electronic annotators that use ISS annotations to make predictions should be viewed sceptically. We recommend that curators thoroughly review ISS annotations before accepting them as valid. Overall, users of curated sequence annotations from the GO database should feel assured that they are using a comparatively high quality source of information.
Keywords: Data Interpretation, Statistical
Sensitivity and Specificity
Reproducibility of Results
Sequence Analysis, DNA
Base Sequence
Molecular Sequence Data
Information Storage and Retrieval
Databases, Genetic
Rights: © 2007 Jones et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
DOI: 10.1186/1471-2105-8-170
Published version:
Appears in Collections:Aurora harvest 6
Computer Science publications

Files in This Item:
File Description SizeFormat 
hdl_41351.pdfPublished version422.15 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.