Title
Identifiability of isoform deconvolution from junction arrays and RNA-Seq.
Abstract
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.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.Supplementary data are available at Bioinformatics online.
Year
DOI
Venue
2009
10.1093/bioinformatics/btp544
Bioinformatics
Keywords
Field
DocType
refseq database lead,identifiable gene model,comprehensive splice junction array,isoform deconvolution model,splice junction,splice junction microarrays,splice variant,human exon array,identifiable model,splice junction array,gene expression profiling,alternative splicing,gene selection,rna,computational biology
Gene isoform,RefSeq,splice,Identifiability,Computer science,Exon,Alternative splicing,Bioinformatics,Human genome,Genetics,DNA microarray
Journal
Volume
Issue
ISSN
25
23
1367-4811
Citations 
PageRank 
References 
10
1.17
6
Authors
4
Name
Order
Citations
PageRank
David Hiller1101.17
Hui Jiang220139.94
Weihong Xu3111.56
Wing Hung Wong460796.45