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Comparison of circular RNA prediction tools

Open access
Hansen, Thomas B., Venø, Morten T., Damgaard, Christian K., Kjems, Jørgen·2016·Nucleic Acids Research

Abstract

CircRNAs are novel members of the non-coding RNA family. For several decades circRNAs have been known to exist, however only recently the widespread abundance has become appreciated. Annotation of circRNAs depends on sequencing reads spanning the backsplice junction and therefore map as non-linear reads in the genome. Several pipelines have been developed to specifically identify these non-linear reads and consequently predict the landscape of circRNAs based on deep sequencing datasets. Here, we use common RNAseq datasets to scrutinize and compare the output from five different algorithms; circRNA_finder, find_circ, CIRCexplorer, CIRI, and MapSplice and evaluate the levels of bona fide and false positive circRNAs based on RNase R resistance. By this approach, we observe surprisingly dramatic differences between the algorithms specifically regarding the highly expressed circRNAs and the circRNAs derived from proximal splice sites. Collectively, this study emphasizes that circRNA annotation should be handled with care and that several algorithms should ideally be combined to achieve reliable predictions.

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Metadata

Authors
Hansen, T. B., Venø, M. T., Damgaard, C. K., & Kjems, J.
Venue
Nucleic Acids Research
Published
2015-12-10
Volume
44
Issue
6
Pages
e58-e58
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
OpenAlex
W2194134194
Cited by
395
References
6
FWCI
11.84
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Comparison of circular RNA prediction tools. https://app.cochat.ai/papers/10.1093/nar/gkv1458
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Hansen, T. B., Venø, M. T., Damgaard, C. K., & Kjems, J. (2016). Comparison of circular RNA prediction tools. Nucleic Acids Research. https://doi.org/10.1093/nar/gkv1458

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