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

Genome Biol. 2015 Jan 13;16(1):4. doi: 10.1186/s13059-014-0571-3.


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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Base Sequence
  • Computer Simulation
  • Databases, Nucleic Acid
  • Exons / genetics
  • Exoribonucleases / metabolism
  • Gene Expression Regulation
  • HEK293 Cells
  • HeLa Cells
  • Humans
  • Introns / genetics
  • Molecular Sequence Data
  • RNA / genetics*
  • RNA, Circular
  • Reproducibility of Results
  • Sequence Analysis, RNA
  • Transcriptome / genetics


  • RNA, Circular
  • RNA
  • Exoribonucleases
  • ribonuclease R