Cross-hybridization modeling on Affymetrix exon arrays.
BACKGROUND
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.


BACKGROUND
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/.
Kapur
Karen
K
Department of Statistics, Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA.
Jiang
Hui
H
Xing
Yi
Y
Wong
Wing Hung
WH
D000818:Animals; D001483:Base Sequence; D019295:Computational Biology / Q000379:methods; D030541:Databases, Genetic; D005091:Exons; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D051379:Mice; D015335:Molecular Probes; D008969:Molecular Sequence Data; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012333:RNA, Messenger / Q000235:genetics
D015335:Molecular Probes; D012333:RNA, Messenger