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

Claudio Lorenzi (1) , Sylvain Barriere (1) , Katharina Arnold , Reini Luco (1) , Andrew Oldfield (1) , William Ritchie (1)

1 IGH - Institut de génétique humaine

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.

Domaines: Bio-informatique [q-bio.QM]

Claudio Lorenzi, Sylvain Barriere, Katharina Arnold, Reini Luco, Andrew Oldfield, et al.. IRFinder-S: a comprehensive suite to discover and explore intron retention. Genome Biology, 2021, 22 (1), ⟨10.1186/s13059-021-02515-8⟩. ⟨hal-03422973⟩