Alternative splicing is an important mechanism involved in both health and disease. Recent work highlights the importance of investigating genome-wide changes in patters of splicing and the subsequent functional consequences. Unfortunately current computational methods only support such analysis on a gene-by-gene basis. To fill this gap, we extended IsoformSwitchAnalyzeR thereby enabling analysis of genome-wide changes in both specific types of alternative splicing as well as the predicted functional consequences of the resulting isoform switches. As a case study, we analyzed RNA-seq data from The Cancer Genome Atlas and found systematic changes in both alternative splicing and the consequences of the associated isoform switches.