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CIRI: an efficient and unbiased algorithm for de novo circular RNA identification.

ABSTRACT: Recent studies reveal that circular RNAs (circRNAs) are a novel class of abundant, stable and ubiquitous noncoding RNA molecules in animals. Comprehensive detection of circRNAs from high-throughput transcriptome data is an initial and crucial step to study their biogenesis and function. Here, we present a novel chiastic clipping signal-based algorithm, CIRI, to unbiasedly and accurately detect circRNAs from transcriptome data by employing multiple filtration strategies. By applying CIRI to ENCODE RNA-seq data, we for the first time identify and experimentally validate the prevalence of intronic/intergenic circRNAs as well as fragments specific to them in the human transcriptome.

SUBMITTER: Gao Y

PROVIDER: S-EPMC4316645 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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CIRI: an efficient and unbiased algorithm for de novo circular RNA identification.

Gao Yuan Y Wang Jinfeng J Zhao Fangqing F

Genome biology 20150113

Recent studies reveal that circular RNAs (circRNAs) are a novel class of abundant, stable and ubiquitous noncoding RNA molecules in animals. Comprehensive detection of circRNAs from high-throughput transcriptome data is an initial and crucial step to study their biogenesis and function. Here, we present a novel chiastic clipping signal-based algorithm, CIRI, to unbiasedly and accurately detect circRNAs from transcriptome data by employing multiple filtration strategies. By applying CIRI to ENCOD ...[more]

PMID: 25583365

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