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.
Keywords: Annotation; Differential expression analysis; Functional prediction; R-package; Sequence analysis; circRNA.