Fig. 2

Relationship of SF3B1 expression levels with splicing event patterns of key genes in PDAC. A Volcano-plot where ΔΨ of total events calculated is plotted against the –log10 p-value of the Fisher’s Exact Test to assay differential splicing events between high and low SF3B1 expression groups of samples, showing that SF3B1 tumor expression may influence alternative splicing pattern. B Alternative Splicing event characterization of RNA-seq samples. Total splicing events detected (black) and significantly different events between SF3B1 expression groups (red) are classified depending on their type, showing different frequencies (%) between both conditions. C Significantly different Alternative Splicing Events comparison of PSI values between High and Low expression groups. D KEGG analysis of significantly different spliced genes depending on SF3B1 expression. Ratio of the genes’ hits over the total genes of a pathway (X-axis) is plotted for each pathway (Y-axis). The size of each point denotes the genes hits, and the color represents their significancy. E Reactome analysis of significantly different spliced genes depending on SF3B1 expression. F, G Correlations between SF3B1 and KRAS, CDKN2A, SMAD4, TP53, BRCA1, BRCA2, and HNRNPK mRNA levels in our RNA-seq cohort (F) and PanCancer cohort (G)