Fig. 3

Overview of PAQR. a Read coverage profile of the CD47 terminal exon, whose processing is affected by the knock-down of HNRNPC [19]. b KAPAC-inferred position-dependent activities of the (U)₅ motif based on DaPars-based estimates of relative PAS use (number of PAS n = 13,388) in the same data set as in a. c Sketch of PAQR. 1) Samples with highly biased read coverage along transcripts (low mTIN score), presumably affected by RNA degradation, are identified and excluded from the analysis. 2) Usage of proximal PAS (pPAS) in a sample is determined based on the expected drop in coverage downstream of the used PAS (ratio of the mean squared deviation from mean coverage (MSE) in the full region compared to two distinct regions, split by the poly(A) site). 3) Step 2 is repeated iteratively for subregions bounded by already determined PAS. 4) The consistency between PAS called as used and the global best break points in corresponding regions is evaluated and in case of discrepancy, terminal exons are discarded from the analysis. 5) Relative PAS use is calculated from the average read coverage of individual 3′ UTR segments, each corresponding to the terminal region of an isoform that ends at a used poly(A) site. d Similar HNRNPC activity on PAS use is inferred by KAPAC from estimates of PAS use generated either by PAQR from RNA sequencing data (n = 3599), or measured directly by 3′ end sequencing (Fig. 2e)