The results of the simulation analysis are shown in Figure 2. We observe that Cufflinks performs better than Altrans when the annotation is perfect, but as the percentage of novel transcripts in the simulations increases, Altrans performs better because it suffers less from the imperfect annotation used in the quantification. In comparison, MISO performs less well than both methods. In order to produce a null random distribution for each method, we took the link quantifications for each gene and permutated these for 100 times within the links of this gene. We then measured the correlation of these random assignments with the simulated ones and find that Cufflinks and MISO fall to the levels of random assignment of link quantifications as the novel transcripts increase in the simulations. We estimated the proportion of novel transcripts by using split read mappings from a well-studied LCL transcriptome RNA-sequencing experiment7 and a less well-studied pancreatic beta cell transcriptome RNA-sequencing experiment.25 We observe that in the LCLs on average 25.8% (SD = 3.5%) and in the beta cells 34.7% (SD = 9.3%) of the junctions are not found in the GENCODE v.12 annotation. Therefore we conclude that in RNA-sequencing experiments where the annotation does not fully reflect the underlying isoform variety, Altrans is a sensitive method for quantifying exon junctions.