BACKGROUND: RNA-seq data is currently underutilized, in part because it is 
difficult to predict the functional impact of alternate transcription events. 
Recent software improvements in full-length transcript deconvolution prompted us 
to develop spliceR, an R package for classification of alternative splicing and 
prediction of coding potential.
RESULTS: spliceR uses the full-length transcript output from RNA-seq assemblers 
to detect single or multiple exon skipping, alternative donor and acceptor 
sites, intron retention, alternative first or last exon usage, and mutually 
exclusive exon events. For each of these events spliceR also annotates the 
genomic coordinates of the differentially spliced elements, facilitating 
downstream sequence analysis. For each transcript isoform fraction values are 
calculated to identify transcript switching between conditions. Lastly, spliceR 
predicts the coding potential, as well as the potential nonsense mediated decay 
(NMD) sensitivity of each transcript.
CONCLUSIONS: spliceR is an easy-to-use tool that extends the usability of 
RNA-seq and assembly technologies by allowing greater depth of annotation of 
RNA-seq data. spliceR is implemented as an R package and is freely available 
from the Bioconductor repository ( 
http://www.bioconductor.org/packages/2.13/bioc/html/spliceR.html).