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bioRxiv · 10.1101/2025.04.28.650897

ScIsoX: A Multidimensional Framework for Measuring Transcriptomic Complexity in Single-Cell Long-Read Sequencing Data

Wu, S.·Schmitz, U.
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Abstract

Single-cell isoform sequencing enables high-resolution characterisation of transcript isoform expression, yet analytical frameworks to systematically measure transcriptomic complexity are lacking. Here, we introduce ScIsoX, a computational framework that integrates a novel hierarchical data structure, a suite of complexity metrics, and dedicated visualisation tools for isoform-level analysis. ScIsoX supports systematic exploration of global and cell-type-specific isoform expression patterns arising from alternative splicing, revealing multidimensional complexity signatures across diverse datasets - insights often missed by conventional gene-level approaches.

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Wu, S., Schmitz, U.. 2025-05-01. ScIsoX: A Multidimensional Framework for Measuring Transcriptomic Complexity in Single-Cell Long-Read Sequencing Data. https://doi.org/10.1101/2025.04.28.650897

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