Skip Navigation



Bioinformatics Advance Access published online on October 24, 2009
Bioinformatics, doi:10.1093/bioinformatics/btp613
This Article
Right arrow Advance Access manuscript (PDF)
Right arrow Supplementary Data
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Yang, Y.
Right arrow Articles by Kim, S.
PubMed
Right arrow PubMed Citation
Right arrow Articles by Yang, Y.
Right arrow Articles by Kim, S.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author (2009). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Annotation Confidence Score for Genome Annotation: A Genome Comparison Approach

Youngik Yang 1, Donald Gilbert 2 and Sun Kim 1,*

1 School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA
2 Department of Biology, Indiana University, Bloomington, IN 47408, USA

*To whom correspondence should be addressed. Prof. Sun Kim, E-mail: sun.kim{at}acm.org, sunkim2{at}indiana.edu


  Abstract

Motivation: The massively parallel sequencing technology can be used by small research labs to generate genome sequences of their research interest. However, annotation of genomes still relies on the manual process, which becomes a serious bottleneck to the high throughput genome projects. Recently, automatic annotation methods are increasingly more accurate, but there are several issues. One important challenge in using automatic annotation methods is to distinguish annotation quality of ORFs or genes. The availability of such annotation quality of genes can reduce the human labor cost dramatically since manual inspection can focus only on genes with low annotation quality scores.

Results: In this paper, we propose a novel annotation quality or confidence scoring scheme, called Annotation Confidence Score (ACS), using a genome comparison approach. The scoring scheme is computed by combining sequence and textual annotation similarity using a modified version of a logistic curve. The most important feature of the proposed scoring scheme is to generate a score that reflects the excellence in annotation quality of genes by automatically adjusting the number of genomes used to compute the score and their phylogenetic distance. Extensive experiments with bacterial genomes showed that the proposed scoring scheme generated scores for annotation quality according to the quality of annotation regardless of the number of reference genomes and their phylogenetic distance.

Availability: http://microbial.informatics.indiana.edu/acs.

Contact: sunkim2{at}indiana.edu

Associate Editor: Prof. Dmitrij Frishman

Received on November 17, 2008; revised on October 19, 2009; accepted on October 20, 2009

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.