Gene alternative splicing plays an important role in development, tissue specialization and disease and differences in splicing patterns can reveal important factors for phenotypic differentiation. While multiple computational methods exist to determine splicing differences, there is a need for user-friendly visualizations that present an intuitive view of the data and work across methods.


We developed a toolkit, Jutils, for visualizing differential splicing events at the intron (splice junction) level. Jutils is method-agnostic, converting individual tools’ output into a unified representation and using it to create visualizations. Jutils creates three types of visualizations, namely heatmaps of absolute and Z-score normalized splice ratios, sashimi plots and Venn diagrams of results from multiple comparisons. Jutils is lightweight, relying solely on the unified data file for visualizations.

Availability and implementation

Jutils is implemented in Python and is available from

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