prikaz prve stranice dokumenta A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines
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Scientific paper - Original scientific paper
A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines
Nature methods, - (2025), -; -. https://doi.org/10.1101/2021.04.21.440736
Chen, Ying; Davidson, Nadia M.; Wan, Yuk Kei; Yao, Fei; Su, Yan; Gamaarachchi, Hasindu; Sim, Andre; Patel, Harshil; Low, Hwee Meng; Hendra, Christopher; Wratten, Laura; Hakkaart, Christopher; Sawyer, Chelsea; Iakovleva, Viktoriia; Lee, Puay Leng; Xin, Lixia; Ng, Hui En Vanessa; Loo, Jia Min; Ong, Xuewen; Ng, Hui Qi Amanda; Wang, Jiaxu; Koh, Wei Qian Casslynn; Poon, Suk Yeah Polly; Stanojevic, Dominik; Tran, Hoang-Dai; Lim, Kok Hao Edwin; Toh, Shen Yon; Ewels, Philip Andrew; Ng, Huck-Hui; Iyer, N. Gopalakrishna; Thiery, Alexandre; Chng, Wee Joo; Chen, Leilei; DasGupta, Ramanuj; Sikic, Mile; Chan, Yun-Shen; Tan, Boon Ooi Patrick; Wan, Yue; Tam, Wai Leong; Yu, Qiang; Khor, Chiea Chuan; Wüstefeld, Torsten; Lezhava, Alexander; Pratanwanich, Ploy N.; Love, Michael I.; Goh, Wee Siong Sho; Ng, Sarah B.; Oshlack, Alicia; Iyer, N. Gopalakrishna; Yu, Qiang; Göke, Jonathan More authors...

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Chen, Y., Davidson, N. M., Wan, Y. K., Yao, F., Su, Y., Gamaarachchi, H. ... Göke, J. (2025). A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines. Nature methods, -. (-), -. doi: 10.1101/2021.04.21.440736

Chen, Ying, et al. "A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines." Nature methods, vol. -, no. -, 2025, p. -. https://doi.org/10.1101/2021.04.21.440736

Chen, Ying, Nadia M. Davidson, Yuk Kei Wan, Fei Yao, Yan Su, Hasindu Gamaarachchi, Andre Sim, et al. "A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines." Nature methods -, no. - (2025): -. https://doi.org/10.1101/2021.04.21.440736

Chen, Y., et al. (2025) 'A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines', Nature methods, -(-), p. -. doi: 10.1101/2021.04.21.440736

Chen Y, Davidson NM, Wan YK, Yao F, Su Y, Gamaarachchi H, and sur.. A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines. Nature methods [Internet]. 2025 [cited 2025 April 01];-(-):-. doi: 10.1101/2021.04.21.440736

Y. Chen, et al., "A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines", Nature methods, vol. -, no. -, p. -, 2025. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:168:644152. [Accessed: 01 April 2025]

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Metadata
Title (english)A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines
AuthorYing Chen
AuthorNadia M. Davidson
AuthorYuk Kei Wan
AuthorFei Yao
AuthorYan Su
AuthorHasindu Gamaarachchi
AuthorAndre Sim
AuthorHarshil Patel
AuthorHwee Meng Low
AuthorChristopher Hendra
AuthorLaura Wratten
AuthorChristopher Hakkaart
AuthorChelsea Sawyer
AuthorViktoriia Iakovleva
AuthorPuay Leng Lee
AuthorLixia Xin
AuthorHui En Vanessa Ng
AuthorJia Min Loo
AuthorXuewen Ong
AuthorHui Qi Amanda Ng
AuthorJiaxu Wang
AuthorWei Qian Casslynn Koh
AuthorSuk Yeah Polly Poon
AuthorDominik Stanojevic
AuthorHoang-Dai Tran
AuthorKok Hao Edwin Lim
AuthorShen Yon Toh
AuthorPhilip Andrew Ewels
AuthorHuck-Hui Ng
AuthorN. Gopalakrishna Iyer
AuthorAlexandre Thiery
AuthorWee Joo Chng
AuthorLeilei Chen
AuthorRamanuj DasGupta
AuthorMile Sikic
AuthorYun-Shen Chan
AuthorBoon Ooi Patrick Tan
AuthorYue Wan
AuthorWai Leong Tam
AuthorQiang Yu
AuthorChiea Chuan Khor
AuthorTorsten Wüstefeld
AuthorAlexander Lezhava
AuthorPloy N. Pratanwanich
AuthorMichael I. Love
AuthorWee Siong Sho Goh
AuthorSarah B. Ng
AuthorAlicia Oshlack
AuthorN. Gopalakrishna Iyer
AuthorQiang Yu
AuthorJonathan Göke
Author's institutionUniversity of Zagreb
Faculty of Electrical Engineering and Computing
(Department of Electronic Systems and Information Processing)
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Interdisciplinary Technical Sciences
Abstract (english)
The human genome contains instructions to transcribe more than 200,000 RNAs. However, many RNA transcripts are generated from the same gene, resulting in alternative isoforms that are highly similar and that remain difficult to quantify. To evaluate the ability to study RNA transcript expression, we profiled seven human cell lines with five different RNA-sequencing protocols, including short-read cDNA, Nanopore long-read direct RNA, amplification-free direct cDNA and PCR-amplified cDNA... More sequencing, and PacBio IsoSeq, with multiple spike-in controls, and additional transcriptome-wide N6-methyladenosine profiling data. We describe differences in read length, coverage, throughput and transcript expression, reporting that long-read RNA sequencing more robustly identifies major isoforms. We illustrate the value of the SG-NEx data to identify alternative isoforms, novel transcripts, fusion transcripts and N6-methyladenosine RNA modifications. Together, the SG-NEx data provide a comprehensive resource enabling the development and benchmarking of computational methods for profiling complex transcriptional events at isoform-level resolution. Less
Keywords (english)
Languageenglish
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review - international
Publication versionPublished version
Journal titleNature methods
Numberingvol. -, no. -, p. -, -
p-ISSN1548-7091
e-ISSN1548-7105
DOIhttps://doi.org/10.1101/2021.04.21.440736
URN:NBNurn:nbn:hr:168:644152
Publication2025
Type of resourceText
Access conditionsOpen access
Terms of useLicence Attribution 4.0 International (CC BY 4.0) icon
Created on2025-03-25 12:41:21
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