CIRI3 accelerates circRNA identification in 2,535 cancer samples, suggesting applications for biomarker discovery.
To address recent challenges in circular RNA (circRNA) analysis, we present CIRI3, a tool for circRNA detection and quantification in terabyte-scale RNA-sequencing datasets. Using dynamic multithreaded task partitioning and a blocking search strategy for junction reads, CIRI3 is an order of magnitude faster than existing tools, while providing increased accuracy. We identified differentially spliced circRNAs across 2,535 cancer-related samples, and constructed a pretraining model and a biomarker network provided as the CIRIonco database. CIRI3 speeds up circRNA detection with low memory requirements.
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Zheng et al. (2025) studied this question.
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