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Nucleic Acids Research 2005 33(22):7120-7128; doi:10.1093/nar/gki1020
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Published online 16 December 2005

© The Author 2005. Published by Oxford University Press. All rights reserved
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions{at}oxfordjournals.org

Article

Automatic assessment of alignment quality

Timo Lassmann* and Erik L. L. Sonnhammer

Center for Genomics and Bioinformatics, Karolinska Institutet S-17177 Stockholm, Sweden

*To whom correspondence should be addressed. Tel: +46 8 5248 6372; Fax: +46 8 337983; Email: timo.lassmann{at}cgb.ki.se

Received September 8, 2005. Revised October 21, 2005. Accepted November 30, 2005.

Multiple sequence alignments play a central role in the annotation of novel genomes. Given the biological and computational complexity of this task, the automatic generation of high-quality alignments remains challenging. Since multiple alignments are usually employed at the very start of data analysis pipelines, it is crucial to ensure high alignment quality. We describe a simple, yet elegant, solution to assess the biological accuracy of alignments automatically. Our approach is based on the comparison of several alignments of the same sequences. We introduce two functions to compare alignments: the average overlap score and the multiple overlap score. The former identifies difficult alignment cases by expressing the similarity among several alignments, while the latter estimates the biological correctness of individual alignments. We implemented both functions in the MUMSA program and demonstrate the overall robustness and accuracy of both functions on three large benchmark sets.


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