Specific identification and quantification of circular RNAs from sequencing data

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Detecting circular RNAs: bioinformatic and experimental challenges (2016, background): “As most algorithms do not control false positives that occur at canonical sequence motifs, many algorithms additionally apply (high) thresholds on absolute read count 3,4,7,27,28 or on counts relative to linear reads from the host gene 26 .”
CircAtlas: an integrated resource of one million highly accurate circular RNAs from 1070 vertebrate transcriptomes (2020, methodology): “Briefly, the circRNAs in each species were identified using four detection algorithms, including CIRI2 [26, 27], find_circ [6], CIRCexplorer2 [28], and DCC [29], which have been widely used and extensively tested by previous studies [1, 30 – 32].”
The bioinformatics toolbox for circRNA discovery and analysis (2020, methodology): “In contrast to tools that support raw RNA-Seq reads, DCC and CircTest [47] use the output of STAR read mapper to identify BSJ reads.”