Work

ScIsoX: a multidimensional framework for measuring isoform-level transcriptomic complexity in single cells

Year: 2025

Type: article

Abstract: Single-cell isoform analysis enables high-resolution characterization of transcript 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 visualization 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. We demonstrate the utility of ScIsoX across multiple real-world single-cell isoform sequencing datasets, showcasing its potential as a general framework for transcriptomic complexity analysis.

Source: Genome biology

DOI: 10.1186/s13059-025-03758-5

Authors: Siyuan Wu, Ulf Schmitz

Institutions: Monash University, James Cook University

Language: English

Topic: Single-cell and spatial transcriptomics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $5,490

Funders: Townsville Hospital and Health Service, Medical Research Council, National Health and Medical Research Council