title: Detecting circular RNAs: bioinformatic and experimental challenges.
abstract: The pervasive expression of circular RNAs (circRNAs) is a recently discovered feature of gene expression in highly diverged eukaryotes. Numerous algorithms that are used to detect genome-wide circRNA expression from RNA sequencing (RNA-seq) data have been developed in the past few years, but there is little overlap in their predictions and no clear gold-standard method to assess the accuracy of these algorithms. We review sources of experimental and bioinformatic biases that complicate the accurate discovery of circRNAs and discuss statistical approaches to address these biases. We conclude with a discussion of the current experimental progress on the topic.
authors.affiliation: Stanford Biomedical Informatics Training Program, Stanford, California 94305, USA.
authors.forename: Linda
authors.initials: L
authors.lastname: Szabo
authors.affiliation: Stanford Department of Biochemistry, Department of Biomedical Data Science, Stanford Cancer Institute, Stanford, California 94305, USA.
authors.forename: Julia
authors.initials: J
authors.lastname: Salzman
mesh_terms: D019295:Computational Biology / Q000379:methods*; D030561:Databases, Nucleic Acid; D006801:Humans; D058977:Molecular Sequence Annotation / Q000379:methods / Q000706:statistics & numerical data*; D012313:RNA / Q000737:chemistry / Q000378:metabolism*; D000079962:RNA, Circular; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software
chemical_list: D000079962:RNA, Circular; D012313:RNA