Figure 1

Quantification schema. A simplified gene model consists of two expressed isoforms (Top). Exons are colored according to the isoform of origin. Two model types used for quantification purpose (Bottom). In the count-based models (left), reads are assigned to counting units (shown by dash lines) without ambiguity. For each counting unit the model can be viewed as a test on two possible outcomes (spliced in or spliced out). The isoform resolution model is shown on the right where two ends of a read pair (show as dark solid boxes connected by curly dash line) align upstream and downstream of an alternative donor site. l _i1(f) is the length of alignment of fragment f to isoform i1, and is shorter than l _i2(f). Therefore if the fragment size distribution is known, it is possible to infer which isoform is more likely to generate f. Note that transcript effective length, i.e. l _i1(f), l _i2(f) and other parameters (depends on model you use) might also affect the probability of assigning reads to isoforms. Usually a maximum likelihood based approach is used to optimize this probability.