Quantification of transcript isoforms at the single-cell level using SCALPEL

Abstract

This study presents SCALPEL, a computational framework for quantifying transcript isoforms at single-cell resolution. The method enables detailed analysis of isoform diversity and regulation in complex biological systems.

Key Highlights

• Novel approach for single-cell isoform quantification
• Comprehensive analysis pipeline for alternative polyadenylation
• Scalable implementation compatible with modern scRNA-seq datasets
• Open-source software with reproducible workflows

Links

• Paper (Nature Communications)
• Code (GitHub)
• Zenodo Archive

Citation

Citations: 2 (Google Scholar)

@article{ake2025scalpel,
  title={Quantification of transcript isoforms at the single-cell level using SCALPEL},
  author={Ake, Franz and Schilling, M and Fern{\'a}ndez-Moya, SM and Jaya Ganesh, A and others},
  journal={Nature Communications},
  volume={16},
  number={1},
  pages={6402},
  year={2025},
  publisher={Nature Publishing Group}
}

Recommended citation: Ake, F., Schilling, M., Fernández-Moya, S.M., Jaya Ganesh, A., et al. (2025). Quantification of transcript isoforms at the single-cell level using SCALPEL. Nature Communications, 16(1), 6402.
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