circRNAprofiler: an R-based computational framework for the downstream analysis of circular RNAs

Simona Aufiero; Yolan J. Reckman; Anke J. Tijsen; Yigal M. Pinto; Esther E. Creemers

doi:https://doi.org/10.1186/s12859-020-3500-3

circRNAprofiler: an R-based computational framework for the downstream analysis of circular RNAs

Simona Aufiero, Yolan J. Reckman, Anke J. Tijsen, Yigal M. Pinto, Esther E. Creemers

Research output: Contribution to journal › Article › Academic › peer-review

12 Citations (Scopus)

Abstract

BACKGROUND: Circular RNAs (circRNAs) are a newly appreciated class of non-coding RNA molecules. Numerous tools have been developed for the detection of circRNAs, however computational tools to perform downstream functional analysis of circRNAs are scarce. RESULTS: We present circRNAprofiler, an R-based computational framework that runs after circRNAs have been identified. It allows to combine circRNAs detected by multiple publicly available annotation-based circRNA detection tools and to analyze their expression, genomic context, evolutionary conservation, biogenesis and putative functions. CONCLUSIONS: Overall, the circRNA analysis workflow implemented by circRNAprofiler is highly automated and customizable, and the results of the analyses can be used as starting point for further investigation in the role of specific circRNAs in any physiological or pathological condition.

Original language	English
Article number	164
Pages (from-to)	164
Number of pages	1
Journal	BMC Bioinformatics
Volume	21
Issue number	1
DOIs	https://doi.org/10.1186/s12859-020-3500-3
Publication status	Published - 29 Apr 2020

Keywords

Annotation
Differential expression analysis
Functional prediction
R-package
Sequence analysis
circRNA

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Cite this

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title = "circRNAprofiler: an R-based computational framework for the downstream analysis of circular RNAs",

abstract = "BACKGROUND: Circular RNAs (circRNAs) are a newly appreciated class of non-coding RNA molecules. Numerous tools have been developed for the detection of circRNAs, however computational tools to perform downstream functional analysis of circRNAs are scarce. RESULTS: We present circRNAprofiler, an R-based computational framework that runs after circRNAs have been identified. It allows to combine circRNAs detected by multiple publicly available annotation-based circRNA detection tools and to analyze their expression, genomic context, evolutionary conservation, biogenesis and putative functions. CONCLUSIONS: Overall, the circRNA analysis workflow implemented by circRNAprofiler is highly automated and customizable, and the results of the analyses can be used as starting point for further investigation in the role of specific circRNAs in any physiological or pathological condition.",

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T1 - circRNAprofiler: an R-based computational framework for the downstream analysis of circular RNAs

AU - Aufiero, Simona

AU - Reckman, Yolan J.

AU - Tijsen, Anke J.

AU - Pinto, Yigal M.

AU - Creemers, Esther E.

PY - 2020/4/29

Y1 - 2020/4/29

N2 - BACKGROUND: Circular RNAs (circRNAs) are a newly appreciated class of non-coding RNA molecules. Numerous tools have been developed for the detection of circRNAs, however computational tools to perform downstream functional analysis of circRNAs are scarce. RESULTS: We present circRNAprofiler, an R-based computational framework that runs after circRNAs have been identified. It allows to combine circRNAs detected by multiple publicly available annotation-based circRNA detection tools and to analyze their expression, genomic context, evolutionary conservation, biogenesis and putative functions. CONCLUSIONS: Overall, the circRNA analysis workflow implemented by circRNAprofiler is highly automated and customizable, and the results of the analyses can be used as starting point for further investigation in the role of specific circRNAs in any physiological or pathological condition.

AB - BACKGROUND: Circular RNAs (circRNAs) are a newly appreciated class of non-coding RNA molecules. Numerous tools have been developed for the detection of circRNAs, however computational tools to perform downstream functional analysis of circRNAs are scarce. RESULTS: We present circRNAprofiler, an R-based computational framework that runs after circRNAs have been identified. It allows to combine circRNAs detected by multiple publicly available annotation-based circRNA detection tools and to analyze their expression, genomic context, evolutionary conservation, biogenesis and putative functions. CONCLUSIONS: Overall, the circRNA analysis workflow implemented by circRNAprofiler is highly automated and customizable, and the results of the analyses can be used as starting point for further investigation in the role of specific circRNAs in any physiological or pathological condition.

KW - Annotation

KW - Differential expression analysis

KW - Functional prediction

KW - R-package

KW - Sequence analysis

KW - circRNA

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circRNAprofiler: an R-based computational framework for the downstream analysis of circular RNAs

Abstract

Keywords

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