ScanExitronLR: characterization and quantification of exitron splicing events in long-read RNA-seq data

Fry, J. P.; Li, Y.; Yang, R.

doi:10.1101/2022.03.25.485864

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bioRxiv · 10.1101/2022.03.25.485864

ScanExitronLR: characterization and quantification of exitron splicing events in long-read RNA-seq data

Fry, J. P.·Li, Y.·Yang, R.

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Abstract

SummaryExitron splicing is a type of alternative splicing where coding sequences are spliced out. Recently, exitron splicing has been shown to increase proteome plasticity and play a role in cancer. Long-read RNA-seq is well suited for quantification and discovery of alternative splicing events; however, there are currently no tools available for detection and annotation of exitrons in long-read RNA-seq data. Here we present ScanExitronLR, an application for the characterization and quantification of exitron splicing events in long-reads. From a BAM alignment file, reference genome and reference gene annotation, ScanExitronLR outputs exitron events at the transcript level. Outputs of ScanExitronLR can be used in downstream analyses of differential exitron splicing. A companion tool, AnnotateExitron, reports exitron annotations such as truncation or frameshift type, nonsense-mediated decay status, and Pfam domain interruptions. We demonstrate that ScanExitronLR performs better on noisy long-reads than currently published exitron detection algorithms designed for short-read data. Availability and ImplementationScanExitronLR is freely available at https://github.com/ylab-hi/ScanExitronLR and distributed as a pip package on the Python Package Index. Contactyang4414@umn.edu Supplementary InformationSupplementary data are available at Bioinformatics online.

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Fry, J. P., Li, Y., Yang, R.. 2022-03-27. ScanExitronLR: characterization and quantification of exitron splicing events in long-read RNA-seq data. https://doi.org/10.1101/2022.03.25.485864

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