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Bioinformatics. 2008 Dec 15;24(24):2887-93. doi: 10.1093/bioinformatics/btn571. Epub 2008 Nov 4.

Cross-hybridization modeling on Affymetrix exon arrays.

Author information

  • 1Department of Statistics, Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA.

Abstract

MOTIVATION:

Microarray designs have become increasingly probe-rich, enabling targeting of specific features, such as individual exons or single nucleotide polymorphisms. These arrays have the potential to achieve quantitative high-throughput estimates of transcript abundances, but currently these estimates are affected by biases due to cross-hybridization, in which probes hybridize to off-target transcripts.

RESULTS:

To study cross-hybridization, we map Affymetrix exon array probes to a set of annotated mRNA transcripts, allowing a small number of mismatches or insertion/deletions between the two sequences. Based on a systematic study of the degree to which probes with a given match type to a transcript are affected by cross-hybridization, we developed a strategy to correct for cross-hybridization biases of gene-level expression estimates. Comparison with Solexa ultra high-throughput sequencing data demonstrates that correction for cross-hybridization leads to a significant improvement of gene expression estimates.

AVAILABILITY:

We provide mappings between human and mouse exon array probes and off-target transcripts and provide software extending the GeneBASE program for generating gene-level expression estimates including the cross-hybridization correction http://biogibbs.stanford.edu/~kkapur/GeneBase/.

PMID:
18984598
[PubMed - indexed for MEDLINE]
PMCID:
PMC2639301
Free PMC Article

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