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Bioinformatics 2007 23(13):i195-i204; doi:10.1093/bioinformatics/btm200
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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.

Optimized design and assessment of whole genome tiling arrays

Stefan Gräf 1, Fiona G. G. Nielsen 2,4, Stefan Kurtz 3, Martijn A. Huynen 4, Ewan Birney 1, Henk Stunnenberg 2 and Paul Flicek 1,*

1EMBL–European Bioinformatics Institute, Hinxton, Cambridge, UK2Nijmegen Center for Molecular Life Sciences, Radboud University Nijmegen, The Netherlands3Center for Bioinformatics, University of Hamburg, Germany4Nijmegen Center for Molecular Life Sciences, Radboud University Nijmegen Medical Center, The Netherlands

*To whom correspondence should be addressed.


  Abstract

Motivation: Recent advances in microarray technologies have made it feasible to interrogate whole genomes with tiling arrays and this technique is rapidly becoming one of the most important high-throughput functional genomics assays. For large mammalian genomes, analyzing oligonucleotide tiling array data is complicated by the presence of non-unique sequences on the array, which increases the overall noise in the data and may lead to false positive results due to cross-hybridization. The ability to create custom microarrays using maskless array synthesis has led us to consider ways to optimize array design characteristics for improving data quality and analysis. We have identified a number of design parameters to be optimized including uniqueness of the probe sequences within the whole genome, melting temperature and self-hybridization potential.

Results: We introduce the uniqueness score, U, a novel quality measure for oligonucleotide probes and present a method to quickly compute it. We show that U is equivalent to the number of shortest unique substrings in the probe and describe an efficient greedy algorithm to design mammalian whole genome tiling arrays using probes that maximize U. Using the mouse genome, we demonstrate how several optimizations influence the tiling array design characteristics. With a sensible set of parameters, our designs cover 78% of the mouse genome including many regions previously considered ‘untilable’ due to the presence of repetitive sequence. Finally, we compare our whole genome tiling array designs with commercially available designs.

Availability: Source code is available under an open source license from http://www.ebi.ac.uk/~graef/arraydesign/

Contact: flicek{at}ebi.ac.uk


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