ArticleNucleic acids research2023
CYCLeR-a novel tool for the full isoform assembly and quantification of circRNAs.
Article in Nucleic acids research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Review
- AQUARIUM_HB: a bioinformatics pipeline for human blood circular RNA analysis.Non-coding RNA research · 2026Article
- EIciRNAs in focus: current understanding and future perspectives.RNA biology · 2025Review
- Accurate Reconstruction of Circular RNAs from Complex Rolling Circular Long Reads with CircPlex.bioRxiv : the preprint server for biology · 2025Article
- Circular RNAs in Cardiovascular Physiopathology: From Molecular Mechanisms to Therapeutic Opportunities.International journal of molecular sciences · 2025Review
- Accurate assembly of circular RNAs with TERRACE.Genome research · 2024Article
- Computational approaches and challenges in the analysis of circRNA data.BMC genomics · 2024Review
- Systematic identification and characterization of exon-intron circRNAs.Genome research · 2024Article
- An updated database of virus circular RNAs provides new insights into the biogenesis mechanism of the molecule.Emerging microbes & infections · 2023Article
- New insight into circRNAs: characterization, strategies, and biomedical applications.Experimental hematology & oncology · 2023Review
- Large-scale benchmarking of circRNA detection tools reveals large differences in sensitivity but not in precision.Nature methods · 2023Article
- Computational approaches for circRNAs prediction and in silico characterization.Briefings in bioinformatics · 2023Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Splicing is one key mechanism determining the state of any eukaryotic cell. Apart from linear splice variants, circular splice variants (circRNAs) can arise via non-canonical splicing involving a back-splice junction (BSJ). Most existing methods only identify circRNAs via the corresponding BSJ, but do not aim to estimate their full sequence identity or to identify different, alternatively spliced circular isoforms arising from the same BSJ. We here present CYCLeR, the first computational method for identifying the full sequence identity of new and alternatively spliced circRNAs and their abundances while simultaneously co-estimating the abundances of known linear splicing isoforms. We show that CYCLeR significantly outperforms existing methods in terms of F score and quantification of transcripts in simulated data. In a in a comparative study with long-read data, we also show the advantages of CYCLeR compared to existing methods. When analysing Drosophila melanogaster data, CYCLeR uncovers biological patterns of circRNA expression that other methods fail to observe.
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