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Bioinformatics Advance Access published online on July 29, 2004
Bioinformatics, doi:10.1093/bioinformatics/bth439
Bioinformatics © Oxford University Press 2004; all rights reserved
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Received May 29, 2004
Revised July 23, 2004
Accepted July 24, 2004

Article

Primer design and marker clustering for multiplex SNP-IT primer extension genotyping assay using statistical modeling

Anton Yuryev 1*, Jianping Huang 2, Kathryn E. Scott 3, Jennifer Kuebler , Miriam Donaldson , Michael S. Phillips 4, Mark Pohl 5, Michael T. Boyce-Jacino 6

1 Ariadne Genomics Inc, Rockville, MD 20850, USA
2 New Jersey Department of Health, Trenton, NJ USA
3 Center for Translational Medicine, Philadelphia, PA USA
4 Genome Quebec and McGill University Genome Center, Montreal H3A 1A4, Canada
5 University of Maryland, Baltimore, MD 21201, USA
6 Beckman Coulter Inc., Princeton, NJ USA

* To whom correspondence should be addressed. E-mail: ayuryev{at}ariadnegenomics.com.


  Abstract

Motivation: The optimization of the primer design is critical for the development of high-throughput SNP genotyping methods. Recently developed statistical models of the SNP-IT primer extension genotyping reaction allow further improvement of primer quality for the assay.

Results: Here we describe how the statistical models can be used to improve primer design for the assay. We also show how to optimize clustering of the SNP markers into multiplex panels using statistical model for multiplex SNP-IT. The primer set failure probability calculated by a model is used as a minimization function for both primer selection and primers clustering. Three clustering algorithms for the multiplex genotyping SNP-IT assay are described and their relative performance is evaluated. We also describe the approaches to improve the speed of primer design and clustering calculations when using the statistical models. Our clustering decreases the average failure probability of the marker set by 7-25%. The experimental marker failure rate in the multiplex reaction was reduced dramatically and success rate can be achieved as high as 96%.

Availability: The primer design using statistical models is freely available from www.autoprimer.com.


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