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Bioinformatics Advance Access published online on January 10, 2006
Bioinformatics, doi:10.1093/bioinformatics/btk028
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received November 15, 2005
Revised December 21, 2005
Accepted December 23, 2005

Article

Inferring global levels of alternative splicing isoforms using a generative model of microarray data

Ofer Shai 1 *, Quaid D. Morris 2, Benjamin J. Blencowe 2, and Brendan J. Frey 1

1 Dept. of Electrical and Computer Engineering, University of Toronto, Toronto, Canada, M5S 3G8
2 Banting and Best Dept. of Medical Research, University of Toronto, Toronto, Canada, M5G 1L6

* To whom correspondence should be addressed.
Ofer Shai, E-mail: ofer{at}psi.toronto.edu


  Abstract

Motivation: Alternative splicing (AS) is a frequent step in metozoan gene expression whereby the exons of genes are spliced in different combinations to generate multiple isoforms of mature mRNA. AS functions to enrich an organism's proteomic complexity and regulates gene expression. Despite its importance, the mechanisms underlying AS and its regulation are not well understood, especially in the context of global gene expression patterns. We present here an algorithm referred to as the Generative model for the Alternative Splicing Array Platform (GenASAP) that can predict the levels of AS for thousands of exon skipping events using data generated from custom microarrays. GenASAP uses Bayesian learning in an unsupervised probability model to accurately predict AS levels from the microarray data. GenASAP is capable of learning the hybridization profiles of microarray data, while modeling noise processes and missing or aberrant data. GenASAP has been successfully applied to the global discovery and analysis of AS in mammalian cells and tissues.

Results: GenASAP was applied to data obtained from a custom microarray designed for the monitoring of 3,126 AS events in mouse cells and tissues. The microarray design included probes specific for exon body and junction sequences formed by the splicing of exons. Our results show that GenASAP provides accurate predictions for over one third of the total events, as verified by independent RT-PCR assays.

Supplementary information: http://www.psi.toronto.edu/GenASAP.


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