Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
Bioinformatics and Computational Biology Program, University of Minnesota, Minneapolis, MN 55455, USA.
Bioinformatics. 2022 Oct 31;38(21):4966-4968. doi: 10.1093/bioinformatics/btac626.
Exitron 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 the 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 individual transcript level. Outputs of ScanExitronLR can be used in downstream analyses of differential exitron splicing. In addition, ScanExitronLR optionally 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.
ScanExitronLR is freely available at https://github.com/ylab-hi/ScanExitronLR and distributed as a pip package on the Python Package Index.
Supplementary data are available at Bioinformatics online.
外显子剪接是一种编码序列被剪接出去的选择性剪接。最近，外显子剪接被证明可以增加蛋白质组的可塑性，并在癌症中发挥作用。长读长 RNA-seq 非常适合定量和发现选择性剪接事件；然而，目前还没有工具可用于检测和注释长读长 RNA-seq 数据中的外显子。在这里，我们介绍了 ScanExitronLR，这是一种用于在长读长中表征和定量外显子剪接事件的应用程序。从 BAM 比对文件、参考基因组和参考基因注释中，ScanExitronLR 以单个转录本水平输出外显子事件。ScanExitronLR 的输出可用于下游差异外显子剪接分析。此外，ScanExitronLR 还可以报告外显子注释，如截断或移码类型、无义介导的衰变状态和 Pfam 结构域中断。我们证明，ScanExitronLR 在嘈杂的长读长上的性能优于目前为短读长数据设计的已发布的外显子检测算法。
ScanExitronLR 可在 https://github.com/ylab-hi/ScanExitronLR 上免费获得，并作为 Python 包索引上的 pip 包分发。
补充数据可在生物信息学在线获得。
