Applied Mathematician | Biological Mathematics | PhD in Applied Maths @MonashUni | Postdoc @ulfschmitz team | Lecturer @JCU
Siyuan Thaddeus Wu
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.
‼️ 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.
Siyuan Thaddeus Wu
Siyuan Thaddeus Wu
Siyuan Thaddeus Wu
Siyuan Thaddeus Wu
ScIsoX: A Multidimensional Framework for Measuring Transcriptomic Complexity in Single-Cell Long-Read Sequencing Data https://www.biorxiv.org/content/10.1101/2025.04.28.650897v1
