Sensitive, reliable, and robust circRNA detection from RNA-seq with CirComPara2

Current methods for the identification of circular RNAs (circRNAs) suffer from low discovery rates and inconsistent performance in diverse data sets. Therefore, the applied detection algorithm can bias high-throughput study findings by missing relevant circRNAs. Here, we show that our bioinformatics tool CirComPara2 (https://github.com/egaffo/CirComPara2), by combining multiple circRNA detection methods, consistently achieves high recall rates without loss of precision in simulated and different real data sets.