AQUARIUM: accurate quantification of circular isoforms using model-based strategy.

Abstract

Currently, most computational methods estimate the expression of circular RNAs (circRNAs) using the number of sequencing reads that support back-splicing junctions (BSJ) in RNA-seq data, which may introduce biased estimation of circRNA expression due to the uneven distribution of sequencing reads. To overcome this, we previously developed a model-based strategy for circRNA quantification, enabling consideration of sequencing reads from the entire transcript. Yet, the lack of exact transcript structure of circRNAs may limit its accuracy. Here, we proposed a substantially improved circRNA quantification tool, AQUARIUM, by introducing the full-length RNA structure of circular isoforms. We assessed its performance in circRNA quantification using both biological and simulated rRNA-depleted RNA-seq datasets, and demonstrated its superior performance at both BSJ and isoform level. AQUARIUM is freely available at https://github.com/wanjun-group-seu/AQUARIUM. Supplementary data are available at Bioinformatics online.