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Updated: Sep 13, 2025

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
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Selecting differential splicing methods: Practical considerations for short-read RNA sequencing.

Ben J Draper1, Mark J Dunning2, David C James1

  • 1Department of Chemical and Biological Engineering, Mappin St., The University of Sheffield, Sheffield, S1 3JD, UK.

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|July 31, 2025
PubMed
Summary
This summary is machine-generated.

This review examines bioinformatics tools for analyzing alternative splicing from RNA sequencing data. It highlights challenges and recommends tools like DEXSeq and rMATS for researchers, considering data input and analysis needs.

Keywords:
Alternative SplicingBioinformaticsDifferential ExpressionRNASeqTranscriptomics

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Area of Science:

  • Bioinformatics
  • Genomics
  • Molecular Biology

Background:

  • Alternative splicing is a key mechanism in gene regulation with significant clinical and biotechnological relevance.
  • Investigating differential splicing requires specialized bioinformatics tools to analyze RNA sequencing (RNA-seq) data.

Purpose of the Study:

  • To review and categorize bioinformatics tools for short-read RNA-seq analysis of differential splicing.
  • To examine the statistical methods, applications, and benefits of these tools.
  • To provide guidance for selecting appropriate tools based on research needs.

Main Methods:

  • A comprehensive review of 22 bioinformatics tools for differential splicing analysis.
  • Categorization of tools based on statistical approaches (parametric, non-parametric, probabilistic) and analysis levels (transcript, exon, event).
  • Evaluation of tool performance through benchmarking studies and consideration of citation frequency and maintenance.

Main Results:

  • Significant challenges exist in splice site identification and isoform deconvolution for alternative splicing quantification.
  • Benchmarking studies reveal considerable variability in tool performance across different datasets and scenarios, with no universal consensus.
  • Tools such as DEXSeq and rMATS are frequently cited and actively maintained, making them recommended choices.

Conclusions:

  • Selecting the right bioinformatics tool for alternative splicing analysis is critical and depends on data input and desired analysis level.
  • A proposed guide schematic aids researchers in tool selection.
  • Emerging long-read RNA sequencing technologies offer complementary approaches with potential to simplify isoform deconvolution and drive further innovation.