Circular RNAs (circRNAs) are emerging species of mRNA splicing products with largely unknown functions. Although several computational pipelines for circRNA identification have been developed, these methods strictly rely on uniquely mapped reads overlapping back-splice junctions (BSJs) and lack approaches to model the statistical significance of the identified circRNAs. Here, we reported a systematic computational approach to identify circRNAs by simultaneously utilizing BSJ overlapping reads and discordant BSJ spanning reads to identify circRNAs. Moreover, we developed a novel procedure to estimate the P-values of the identified circRNAs. A computational cross-validation and experimental validations demonstrated that our method performed favorably compared to existing circRNA detection tools. We created a standalone tool, CircRNAFisher, to implement the method, which might be valuable to computational and experimental scientists studying circRNAs.

中文翻译：

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CircRNAFisher：一种用于从头进行环形RNA鉴定的系统计算方法。

环状RNA（circRNA）是功能未知的新兴的mRNA剪接产物。尽管已经开发了几种用于circRNA识别的计算流程，但是这些方法严格依赖于唯一映射的读段重叠的反向剪接连接（BSJ），并且缺乏对已识别circRNA的统计意义进行建模的方法。在这里，我们报告了一种系统化的计算方法，可通过同时利用BSJ重叠阅读和不一致的BSJ跨度阅读来识别circRNA来识别circRNA。此外，我们开发了一种新颖的程序来估计已鉴定的circRNA的P值。计算机交叉验证和实验验证表明，与现有circRNA检测工具相比，我们的方法表现出色。我们创建了一个独立工具CircRNAFisher，