Accurate Assembly of Circular RNAs with TERRACE

Tasfia Zahin, Qian Shi, Xiaofei Carl Zang, Mingfu Shao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Circular RNA (circRNA) is a class of RNA molecules that forms a closed loop with its 5’ and 3’ ends covalently bonded. CircRNAs were severely overlooked previously owing to the biases in the RNA-seq protocols and in the detection algorithms, but recently gained tremendous attentions in both aspects. Most existing methods for assembling circRNAs heavily rely on the annotated transcriptomes, and hence exhibit unsatisfactory accuracy when a high-quality annotation is unavailable. Here we present TERRACE, a new algorithm for full-length assembly of circRNAs from paired-end total RNA-seq data. TERRACE is compared with leading circRNA detection methods on both simulations and biological datasets. Our method consistently outperforms by a large margin in sensitivity while maintaining better or comparable precision. In particular, when the annotations are not provided, TERRACE can assemble 123%–412% more correct circRNAs than state-of-the-art methods on human tissues. TERRACE presents a major leap on assembling full-length circRNAs from RNA-seq data, and we expect it to be widely used in the downstream research on circRNAs. TERRACE is freely available at https://github.com/Shao-Group/TERRACE. The full version of this manuscript is available at https://doi.org/10.1101/2024.02.09.579380.

Original languageEnglish (US)
Title of host publicationResearch in Computational Molecular Biology - 28th Annual International Conference, RECOMB 2024, Proceedings
EditorsJian Ma
PublisherSpringer Science and Business Media Deutschland GmbH
Pages444-447
Number of pages4
ISBN (Print)9781071639887
DOIs
StatePublished - 2024
Event28th International Conference on Research in Computational Molecular Biology, RECOMB 2024 - Cambridge, United States
Duration: Apr 29 2024May 2 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14758 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference28th International Conference on Research in Computational Molecular Biology, RECOMB 2024
Country/TerritoryUnited States
CityCambridge
Period4/29/245/2/24

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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