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Bioinformatics Advance Access originally published online on July 27, 2007
Bioinformatics 2007 23(18):2488-2490; doi:10.1093/bioinformatics/btm366
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© 2007 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.

Quality estimation of multiple sequence alignments by Bayesian hypothesis testing

Andrija Tomovic and Edward J. Oakeley *

Friedrich Miescher Institute for Biomedical Research, Novartis Research Foundation, Maulbeerestrasse 66, CH-4056 Basel

*To whom correspondence should be addressed.


  Abstract

Summary: In this work we present a web-based tool for estimating multiple alignment quality using Bayesian hypothesis testing. The proposed method is very simple, easily implemented and not time consuming with a linear complexity. We evaluated method against a series of different alignments (a set of random and biologically derived alignments) and compared the results with tools based on classical statistical methods (such as sFFT and csFFT). Taking correlation coefficient as an objective criterion of the true quality, we found that Bayesian hypothesis testing performed better on average than the classical methods we tested. This approach may be used independently or as a component of any tool in computational biology which is based on the statistical estimation of alignment quality.

Availability: http://www.fmi.ch/groups/functional.genomics/tool.htm

Contact: edward.oakeley{at}fmi.ch

Supplementary information: Supplementary data are available from http://www.fmi.ch/groups/functional.genomics/tool-Supp.htm

Associate Editor: Alex Bateman

Received on May 17, 2007; revised on July 2, 2007; accepted on July 9, 2007

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