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Identification of Circular RNAs using RNA Sequencing
Published on: November 14, 2019
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Detecting and quantifying circular RNAs in terabyte-scale RNA-seq datasets with CIRI3.
Xin Zheng1,2, Jinyang Zhang3, Lipu Song1
1China National Center for Bioinformation, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.
Nature Biotechnology
|October 1, 2025
Summary
CIRI3 is a new tool for analyzing circular RNA (circRNA) in large RNA sequencing datasets. It offers faster and more accurate detection and quantification of circRNAs, aiding cancer research.
Area of Science:
- Bioinformatics
- Genomics
- Computational Biology
Background:
- Circular RNA (circRNA) analysis faces challenges with large datasets.
- Accurate detection and quantification of circRNAs are crucial for biological insights.
Purpose of the Study:
- To introduce CIRI3, a novel computational tool for circRNA detection and quantification.
- To enhance the efficiency and accuracy of analyzing terabyte-scale RNA-sequencing data.
Main Methods:
- Developed CIRI3 utilizing dynamic multithreaded task partitioning.
- Implemented a blocking search strategy for efficient junction read processing.
- Applied CIRI3 to analyze 2,535 cancer-related RNA sequencing samples.
Main Results:
- CIRI3 demonstrates an order of magnitude speed improvement over existing tools.
- Achieved increased accuracy in circRNA detection and quantification.
- Identified differentially spliced circRNAs across a large cancer sample cohort.
Conclusions:
- CIRI3 provides a powerful and efficient solution for large-scale circRNA analysis.
- The tool facilitates the discovery of novel circRNA biomarkers.
- The CIRIonco database offers valuable resources for cancer research.
