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April 13, 2026Bioinformatics0 citationsOpen Access

Splitpea: a Python package for protein-protein interaction network rewiring analysis due to alternative splicing

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JZJeffrey ZhongACAlyssa CantuRDRuth Dannenfelser

Key Points

  • The aim is to analyze how alternative splicing events affect protein-protein interaction networks.
  • Utilizes data from skipped exon events via SUPPA2 and rMATS.
  • Processes various input formats including splicing percentages, exon counts, and usage statistics.
  • Generates rewired network graphs and summary statistics for visualization in Cytoscape or Gephi.
  • Produces edge and gene-level summaries of potential PPI changes due to splicing.
  • Identifies disrupted or enhanced PPIs resulting from alternative splicing events.
  • Facilitates easy visualization through user-friendly file formats.

Abstract

Abstract Summary Splitpea takes skipped exon event data at the sample or differential expression level from SUPPA2 and rMATS and maps potential changes to protein-protein interaction (PPI) network rewiring events. It handles a variety of input formats via an easy-to-install Python package, from percent spliced in values comparing two conditions, skipped exon counts, or precalculated exon usage statistics between experimental conditions. In each case, Splitpea produces rewired network graphs, edge and gene-level summary statistics, and Cytoscape or Gephi-ready files for easy visualization, allowing users to find PPIs potentially disrupted or increased by alternative splicing. Availability and Implementation Source code and accompanying documentation can be found on Github ( https://github.com/ylaboratory/splitpea-package ), released under a BSD 3-clause license for open source use, and the Splitpea package is installable via PyPI. Supplementary Information Supplementary material pertaining to the example case studies described herein are made available at Bioinformatics online.

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Cite This Study

Zhong et al. (2026) studied this question.

synapsesocial.com/papers/69dc89473afacbeac03eb06ehttps://doi.org/10.1093/bioinformatics/btag154
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