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.
Highlights
Intron retention (IR) occurs when an intron is transcribed into pre-mRNA and remains in the final mRNA
IRBase enables the visualization and contrast of IR events as well as data sharing It is essential to visualize and contrast specific intron retention events detected by computational approaches before spending resources on their experimental validation
This allows users to understand the transcriptional context of a predicted IR event and to assess whether the event is common to other cell types or specific to their experiment of interest
Summary
Intron retention (IR) occurs when an intron is transcribed into pre-mRNA and remains in the final mRNA. It is a type of alternative splicing that is gaining increased interest in human health and disease research. Detecting IR events poses several specific difficulties. Introns are highly heterogeneous genomic regions, both in length and sequence features. IR levels are generally low and thereby subject to incomplete coverage and higher count overdispersion. Software that is not tuned for IR detection generally performs poorly and databases that provide transcript isoform sequences fail to list many IR events [4, 8]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
