TY - GEN
T1 - Accurate Assembly of Circular RNAs with TERRACE
AU - Zahin, Tasfia
AU - Shi, Qian
AU - Zang, Xiaofei Carl
AU - Shao, Mingfu
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85194224757&partnerID=8YFLogxK
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U2 - 10.1007/978-1-0716-3989-4_49
DO - 10.1007/978-1-0716-3989-4_49
M3 - Conference contribution
AN - SCOPUS:85194224757
SN - 9781071639887
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 444
EP - 447
BT - Research in Computational Molecular Biology - 28th Annual International Conference, RECOMB 2024, Proceedings
A2 - Ma, Jian
PB - Springer Science and Business Media Deutschland GmbH
T2 - 28th International Conference on Research in Computational Molecular Biology, RECOMB 2024
Y2 - 29 April 2024 through 2 May 2024
ER -