Journal Article

Identifiability of isoform deconvolution from junction arrays and RNA-Seq

David Hiller, Hui Jiang, Weihong Xu and Wing Hung Wong

in Bioinformatics

Volume 25, issue 23, pages 3056-3059
Published in print December 2009 | ISSN: 1367-4803
Published online September 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp544
Identifiability of isoform deconvolution from junction arrays and RNA-Seq

More Like This

Show all results sharing this subject:

  • Bioinformatics and Computational Biology

GO

Show Summary Details

Preview

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@stanford.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  3346 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

Full text: subscription required

How to subscribe Recommend to my Librarian

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content.