Wu, S.; Schmitz, U.

Single-cell long-read sequencing enables comprehensive characterisation of full-length transcript isoforms, but lacks robust analytical frameworks for measuring transcriptomic complexity. Here, we introduce ScIsoX, a computational framework that integrates a novel hierarchical data structure, complexity metrics, and visualisation tools for isoform-level investigations. ScIsoX enables systematic interrogation of global and cell-type-specific isoform expression patterns resulting from splicing, revealing distinct complexity signatures across diverse datasets that were previously inaccessible with short-read approaches.