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Optimized design and assessment of whole genome tiling arrays.

Published version
Peer-reviewed

Type

Article

Change log

Authors

Gräf, Stefan 
Nielsen, Fiona GG 
Kurtz, Stefan 
Huynen, Martijn A 
Birney, Ewan 

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/.

Description

Keywords

Algorithms, Chromosome Mapping, Computer-Aided Design, DNA Probes, Equipment Design, Equipment Failure Analysis, Microarray Analysis, Quality Control, Sequence Analysis, DNA

Journal Title

Bioinformatics

Conference Name

Journal ISSN

1367-4803
1367-4811

Volume Title

23

Publisher

Oxford University Press (OUP)