Background: With the increasing depth and decreasing costs of RNA-sequencing researchers are now able to profile the transcriptome with unprecedented detail. These advances not only allow for precise approximation of gene expression levels, but also for the characterization of alternative transcript usage/switching between conditions. 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 transcripts output from RNA-seq assemblers, to detect single- and 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. Furthermore, isoform fraction values are calculated for effective post-filtering, i.e. identification of 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 a easy-to-use tool that allows detection of alternative splicing, transcript switching and NMD sensitivity from RNA-seq data, extending the usability of RNA-seq and assembly technologies. 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).