In eukaryotes, alternative splicing is involved in development, differentiation,1 and disease2 in a tissue-specific manner. Splicing events can be categorized under skipped exon, retained intron, alternative 3′ or 5′ splice sites, mutually exclusive exons, alternative first or last exons, or tandem UTR categories. Before the invention of microarray technology, the proportion of multi-exonic genes undergoing alternative splicing was estimated at approximately 50%.3 However, as the technology improved, these estimates increased to 74% with microarrays4 and to almost 100% with RNA sequencing.5 Although RNA sequencing has been a very powerful tool in discovering unique transcription in tissues and diseases6 and also in elucidating the regulation of transcription,7–10 accurately quantifying transcripts remains a challenge due to the short read length used in most population-based studies. Currently there are multiple transcript quantification methods available including de novo quantification methods like Cufflinks11 and Scripture12 and annotation-based methods like MISO13 and Flux Capacitor.8 However, both approaches have inherent flaws because de novo methods make the assumption that the most parsimonious solution best describes the underlying transcriptome and annotation-based methods assume complete knowledge of the transcriptome, both of which are unlikely to be true.