Fig. 4

Performance of computational methods in identifying variants that affect splicing in the MaPSy challenge. Methods were selected based on the average ranking over three metrics: Pearson’s correlation, Kendall’s tau, and ROC AUC. Scatter plots, Kendell’s tau, and Pearson’s correlation results are shown for in vivo (A, D) and in vitro assays (B, E) separately. The small number of purple points in the scatter plots represent splicing fold changes greater than 1.5-fold. The ROC curve (C) shows performance in variant classification for the two selected methods. The maximum local positive likelihood ratio (\({{\text{lr}}}^{+}\), F) may be large enough for use as auxiliary information, see “ Discussion” (solid line is smoothed fit to the data)