Genome Biology (Nov 2021)

IRFinder-S: a comprehensive suite to discover and explore intron retention

  • Claudio Lorenzi,
  • Sylvain Barriere,
  • Katharina Arnold,
  • Reini F. Luco,
  • Andrew J. Oldfield,
  • William Ritchie

DOI
https://doi.org/10.1186/s13059-021-02515-8
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 13

Abstract

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Abstract Accurate quantification and detection of intron retention levels require specialized software. Building on our previous software, we create a suite of tools called IRFinder-S, to analyze and explore intron retention events in multiple samples. Specifically, IRFinder-S allows a better identification of true intron retention events using a convolutional neural network, allows the sharing of intron retention results between labs, integrates a dynamic database to explore and contrast available samples, and provides a tested method to detect differential levels of intron retention.

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