Recent studies have demonstrated that circular RNAs (circRNAs) are ubiquitous and have diverse functions and mechanisms of biogenesis. In these studies, computational profiling of circRNAs has been prevalently used as an indispensable method to provide high-throughput approaches to detect and analyze circRNAs. However, without an overall understanding of the underlying strategies, these computational methods may not be appropriately selected or used for a specific research purpose, and some misconceptions may result in biases in the analyses. In this review we attempt to illustrate the key steps and summarize tradeoff of different strategies, covering all popular algorithms for circRNA detection and various downstream analyses. We also clarify some common misconceptions and put emphasis on the fields of application for these computational methods.
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