Interested in isoform expression, single-cell analysis, or computational frameworks? Delve into our work at the bioRxiv link.

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.

‼️ ScIsoX: A Framework for Transcriptome Complexity Analysis‼️

In collaboration with Ulf Schmitz (@ulfschmitz.bsky.social), we have developed ScIsoX, the first-ever computational framework specifically designed to characterise transcriptomic complexity in single-cell long-read sequencing data.