We've confirmed its utility across three distinct biological systems, demonstrating how ScIsoX can identify isoform expression patterns in cell populations and at cell-type-specific levels, and characterise the multidimensional nature of transcriptomic complexity.
ScIsoX introduces a novel hierarchical data structure and a comprehensive set of metrics that capture multiple dimensions of isoform expression patterns, revealing insights previously inaccessible with short-read technologies.
Interested in isoform expression, single-cell analysis, or computational frameworks? Delve into our work at the bioRxiv link.