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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/222802
Quantification of transcript isoforms at the single-cell level using SCALPEL
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Single-cell RNA sequencing (scRNA-seq) facilitates the study of transcriptome diversity in individual cells. Yet, many existing methods lack sensitivity and accuracy. Here we introduce SCALPEL, a Nextflow-based tool to quantify and characterize transcript isoforms from standard 3' scRNA-seq data. Using synthetic data, SCALPEL demonstrates higher sensitivity and specificity compared to other tools. In real datasets, SCALPEL predictions have a high agreement with other tools and can be experimentally validated. The use of SCALPEL on real datasets reveals novel cell populations undetectable using single-cell gene expression data, confirms known 3' UTR length changes during cell differentiation, and identifies cell-type specific miRNA signatures regulating isoform expression. Additionally, we show that SCALPEL improves isoform quantification using paired long- and short-read scRNA-seq data. Overall, SCALPEL expands the current scRNA-seq toolkit to explore post-transcriptional gene regulation across species, tissues, and technologies, advancing our understanding of gene regulatory mechanisms at the single-cell level.
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AKE, Franz, et al. Quantification of transcript isoforms at the single-cell level using SCALPEL. Nature Communications. 2025. Vol. 16, num. 1. ISSN 2041-1723. [consulted: 17 of June of 2026]. Available at: https://hdl.handle.net/2445/222802