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Updated: Dec 31, 2025

Identification of Circular RNAs using RNA Sequencing
Published on: November 14, 2019
CIRCexplorer3: A CLEAR Pipeline for Direct Comparison of Circular and Linear RNA Expression
Xu-Kai Ma1, Meng-Ran Wang1, Chu-Xiao Liu2
1CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
Abstract:
Sequences of circular RNAs (circRNAs) produced from back-splicing of exon(s) completely overlap with those from cognate linear RNAs transcribed from the same gene loci with the exception of their back-splicing junction (BSJ) sites. Therefore, examination of global circRNA expression from RNA-seq datasets generally relies on the detection of RNA-seq fragments spanning BSJ sites, which is different from the quantification of linear RNA expression by normalized RNA-seq fragments mapped to whole gene bodies. Thus, direct comparison of circular and linear RNA expression from the same gene loci in a genome-wide manner has remained challenging. Here, we update the previously-reported CIRCexplorer pipeline to version 3 for circular and linear RNA expression analysis from ribosomal-RNA depleted RNA-seq (CIRCexplorer3-CLEAR). A new quantitation parameter, fragments per billion mapped bases (FPB), is applied to evaluate circular and linear RNA expression individually by fragments mapped to circRNA-specific BSJ sites or to linear RNA-specific splicing junction (SJ) sites. Comparison of circular and linear RNA expression levels is directly achieved by dividing FPBcirc by FPBlinear to generate a CIRCscore, which indicates the relative circRNA expression level using linear RNA expression level as the background. Highly-expressed circRNAs with low cognate linear RNA expression background can be readily identified by CIRCexplorer3-CLEAR for further investigation. CIRCexplorer3-CLEAR is publically available at https://github.com/YangLab/CLEAR.
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