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Updated: Jan 16, 2026

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
Published on: June 24, 2021
ScASplicer: An interactive shiny/R application for alternative splicing analysis of single-cell sequencing
Pengwei Hu1, Jixiang Xing2, Wuritu Yang3
1State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, Institutes of Biomedical Sciences, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China; Inner Mongolia Key Laboratory of Life Health and Bioinformatics, School of Life Science and Technology, Inner Mongolia University of Science and Technology, Baotou 014010, China.
This study introduces ScASplicer, a user-friendly tool for analyzing alternative splicing (AS) in single-cell RNA sequencing (scRNA-seq) data. It simplifies complex AS analysis, enhancing transcriptome diversity insights.
Area of Science:
- Genomics
- Computational Biology
- Molecular Biology
Background:
- Alternative splicing (AS) is vital for cellular heterogeneity and transcriptome diversity.
- Analyzing AS in single-cell RNA sequencing (scRNA-seq) data presents significant computational challenges.
- Existing tools lack comprehensive functionality and user-friendliness for scRNA-seq AS analysis.
Purpose of the Study:
- To enhance the usability and functionality of the MARVEL tool for single-cell AS analysis.
- To develop a versatile, code-free platform for exploring AS and gene expression dynamics at the single-cell level.
- To reduce the technical barrier for researchers conducting scRNA-seq AS analysis.
Main Methods:
- Development of a Python package for efficient generation of input files for AS analysis.
- Creation of a Shiny-based R package (ScASplicer) extending MARVEL's capabilities.
- Implementation of interactive, code-free exploration of AS and gene expression for multiple cell populations.
Main Results:
- ScASplicer facilitates easier and more efficient generation of input files for AS analysis.
- The ScASplicer package enables multi-population analysis and interactive exploration of single-cell AS.
- The developed platform significantly improves the user-friendliness of scRNA-seq AS analysis.
Conclusions:
- ScASplicer offers a user-friendly and comprehensive solution for single-cell AS analysis.
- The tool empowers researchers to explore AS and gene expression dynamics more effectively.
- This advancement contributes to a deeper understanding of transcriptome diversity and cell heterogeneity.
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