AQUARIUM: Accurate quantification of circular isoforms using model-based strategy

Guoxia Wen, Musheng Li, Fuyu Li, Zengyan Yang, Tong Zhou, Wanjun Gu

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Summary: 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.

Original languageEnglish (US)
Pages (from-to)4879-4881
Number of pages3
Issue number24
StatePublished - Dec 15 2021

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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