IRFinder-S is a suite of tools to analyse and explore intron retention events in multiple samples. It comprehends:
- IRFinder : detect intron retention from RNA-Seq experiments. Includes an automatic CNN filter that emulate a visual inspection to validate the events.
- IRBase : visualize and share IRFinder's results.
To start using IRFinder, read our wiki user manual.
IRFinder Version 1 is still available at https://github.com/williamritchie/IRFinder but is not anymore maintained.
IRFinder, developed at the Center for Genomic Medicine of Massachusetts General Hospital, the CNRS and the Centenary Institute, implements an end-to-end analysis of intron retention (IR) from mRNA sequencing data in multiple species.
IRFinder includes alignment via the STAR (for short reads) and minimap2 (for long read) algorithm, quality controls on the sample analyzed, IR detection, quantification, convolutional neural network based validation and statistical comparison between multiple samples.
IRFinder was capable of estimating IR events with low coverage or low mappability as confirmed by RT-qPCR.
Before Start: Intron Retention Database - IRBase
Before diving into IRFinder package, users might also consider IRBase. It is a database for human IR inquiry and visualization, based upon pre-calculated IRFinder results from over 935 public available human cell lines RNA-Seq sample.
IRBase allows users to enquire, visualize and download single-gene IR results in a tissue/cell-type of interest, download transcriptome-wide IR results of a sample of interest, upload your results to compare with the public ones and share them with the community.
Lorenzi, C., Barriere, S., Arnold, K. et al. IRFinder-S: a comprehensive suite to discover and explore intron retention. Genome Biol 22, 307 (2021). doi: 10.1186/s13059-021-02515-8
Middleton R*, Gao D*, Thomas A, Singh B, Au A, Wong JJ, Bomane A, Cosson B, Eyras E, Rasko JE, Ritchie W. IRFinder: assessing the impact of intron retention on mammalian gene expression. Genome Biol. 2017 Mar 15;18(1):51. doi: 10.1186/s13059-017-1184-4. PubMed PMID: 28298237.