CircRNAFisher: a systematic computational approach for de novo circular RNA identification.
Acta Pharmacol Sin
; 40(1): 55-63, 2019 Jan.
Article
en En
| MEDLINE
| ID: mdl-30013032
ABSTRACT
Circular RNAs (circRNAs) are emerging species of mRNA splicing products with largely unknown functions. Although several computational pipelines for circRNA identification have been developed, these methods strictly rely on uniquely mapped reads overlapping back-splice junctions (BSJs) and lack approaches to model the statistical significance of the identified circRNAs. Here, we reported a systematic computational approach to identify circRNAs by simultaneously utilizing BSJ overlapping reads and discordant BSJ spanning reads to identify circRNAs. Moreover, we developed a novel procedure to estimate the P-values of the identified circRNAs. A computational cross-validation and experimental validations demonstrated that our method performed favorably compared to existing circRNA detection tools. We created a standalone tool, CircRNAFisher, to implement the method, which might be valuable to computational and experimental scientists studying circRNAs.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
ARN
/
Análisis de Secuencia de ARN
/
Biología Computacional
Tipo de estudio:
Diagnostic_studies
Límite:
Humans
Idioma:
En
Revista:
Acta Pharmacol Sin
Asunto de la revista:
FARMACOLOGIA
Año:
2019
Tipo del documento:
Article
País de afiliación:
China