Simulation Results The general overview of the Altrans algorithm is provided in FigureĀ 1. We first aimed to compare the results between Altrans, Cufflinks, and MISO using simulations. We compared six scenarios, one where the given annotation perfectly described the transcripts in the simulations and five others with 5%, 10%, 25%, 50%, and 75% novel transcripts absent from the annotation (see Material and Methods). Subsequently we quantified the six simulation results with both algorithms using the known annotation in all cases. For MISO we have quantified transcript abundances. This was done to assess how methods performed in cases of complete versus incomplete transcriptome knowledge. The transcript quantifications generated by Cufflinks and MISO were transformed into link quantifications to make them comparable to those generated by Altrans. The results of the simulation analysis are shown in FigureĀ 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.