spliceR: An R package for classification of alternative splicing and prediction of coding potential from RNA-seq data.

With the advent of increasing depth and decreasing costs in digital gene expression technologies exemplified by 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 characterization of alternative isoform usage/switching between samples. Recent software improvements in full transcript deconvolution prompted us to develop spliceR , an R package for classification of alternative splicing. spliceR labels isoforms based on fully assembled transcripts, detecting single- and multiple exon skipping, alternative donor or acceptor sites, intron retention, alternative first or last exon usage, and mutually exclusive exon events. Alongside, event spliced-in/out values are calculated for effective post-filtering, and genomic coordinates of differentially spliced elements are annotated for downstream sequence analysis. Furthermore, spliceR has the option to predict the coding potential and thereby the nonsense mediated decay (NMD) sensitivity of transcripts based on stop codon position.