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Bioinformatics Advance Access originally published online on December 15, 2005
Bioinformatics 2006 22(4):495-496; doi:10.1093/bioinformatics/btk006
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

SEAN: SNP prediction and display program utilizing EST sequence clusters

Derek Huntley 1,*, Angela Baldo 4, Saurabh Johri 2 and Marek Sergot 3

1Centre for Bioinformatics, Division of Molecular Biosciences, Imperial College London SW7 2AZ, UK
2Centre for Molecular Microbiology and Infection, Division of Investigative Sciences, Imperial College London SW7 2AZ, UK
3Department of Computing, Imperial College London SW7 2AZ, UK
4USDA-ARS Plant Genetic Resources Unit, New York State Agricultural Experiment Station Geneva, NY 14456, USA

*To whom correspondence should be addressed.

Summary: SEAN is an application that predicts single nucleotide polymorphisms (SNPs) using multiple sequence alignments produced from expressed sequence tag (EST) clusters. The algorithm uses rules of sequence identity and SNP abundance to determine the quality of the prediction. A Java viewer is provided to display the EST alignments and predicted SNPs.

Availability: SEAN is freely available from http//zebrafish.doc.ic.ac.uk/Sean

Contact: d.huntley{at}imperial.ac.uk

Received on June 29, 2005; revised on November 23, 2005; accepted on December 11, 2005

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