Bioinformatics Advance Access originally published online on September 16, 2009
Bioinformatics 2009 25(23):3056-3059; doi:10.1093/bioinformatics/btp544
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Identifiability of isoform deconvolution from junction arrays and RNA-Seq
1 Department of Statistics, 2 Institute for Computational and Mathematical Engineering, 3 Stanford Genome Technology Center and 4 Department of Health Research and Policy, Stanford University, Stanford, CA 94305, USA
* To whom correspondence should be addressed.
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Abstract |
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Motivation: Splice junction microarrays and RNA-seq are two popular ways of quantifying splice variants within a cell. Unfortunately, isoform expressions cannot always be determined from the expressions of individual exons and splice junctions. While this issue has been noted before, the extent of the problem on various platforms has not yet been explored, nor have potential remedies been presented.
Results: We propose criteria that will guarantee identifiability of an isoform deconvolution model on exon and splice junction arrays and in RNA-Seq. We show that up to 97% of 2256 alternatively spliced human genes selected from the RefSeq database lead to identifiable gene models in RNA-seq, with similar results in mouse. However, in the Human Exon array only 26% of these genes lead to identifiable models, and even in the most comprehensive splice junction array only 69% lead to identifiable models.
Contact: whwong{at}stanford.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.
Associate Editor: Martin Bishop
Received on July 9, 2009; revised on September 8, 2009; accepted on September 9, 2009
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