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Updated: Aug 4, 2025

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
Published on: June 24, 2021
A comprehensive benchmarking of differential splicing tools for RNA-seq analysis at the event level
Minghao Jiang1, Shiyan Zhang1, Hongxin Yin1
1Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 197 Ruijin Er Road, Shanghai 200025, China.
This study benchmarks 21 RNA alternative splicing tools using simulated data, finding significant discrepancies. SUPPA, DARTS, rMATS, and LeafCutter show superior performance for differential splicing detection.
Area of Science:
- Molecular Biology
- Bioinformatics
- Genomics
Background:
- RNA alternative splicing is vital for cellular functions and disease.
- Next-generation sequencing (NGS) enables widespread differential splicing analysis.
- A comprehensive, independent comparison of RNA-seq splicing analysis tools is needed.
Purpose of the Study:
- To systematically evaluate and compare 21 RNA-seq analysis tools for differential splicing events.
- To assess the performance of tools in identifying novel splicing events.
- To propose improved methodologies and a selection protocol for differential splicing analysis.
Main Methods:
- Systematic evaluation of 21 bioinformatic tools using simulated RNA-seq data with known splicing events.
- Assessment of tools' ability to detect novel splice sites.
- Development of methodological approaches including low-expression transcript filtering and tool-pair combination.
- Proposal of a new protocol for selecting tools based on analytical tasks (precision, recall).
Main Results:
- Immense discrepancies were observed among the evaluated tools.
- SUPPA, DARTS, rMATS, and LeafCutter demonstrated superior performance compared to other event-based tools.
- Most event-based tools were found unsuitable for discovering novel splice sites.
- Methodological improvements like transcript filtering and tool-pair combination enhanced overall performance.
Conclusions:
- A standardized protocol for selecting differential splicing analysis tools is proposed.
- The analysis revealed a distinct splicing landscape in the DUX4/IGH subgroup of B-cell acute lymphoblastic leukemia.
- Differential splicing of TCF12 was uncovered in this leukemia subgroup.
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