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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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 Više autora...

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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. -, br. -, 2025, str. -. 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 -, br. - (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, -(-), str. -. doi: 10.1101/2021.04.21.440736

Chen Y, Davidson NM, Wan YK, Yao F, Su Y, Gamaarachchi H, i sur.. A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines. Nature methods [Internet]. 2025. [pristupljeno 26.03.2025.];-(-):-. 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. -, br. -, str. -, 2025. [Online]. Dostupno na: https://urn.nsk.hr/urn:nbn:hr:168:644152. [Citirano: 26.03.2025.]

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Naslov (engleski)A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines
AutorYing Chen
AutorNadia M. Davidson
AutorYuk Kei Wan
AutorFei Yao
AutorYan Su
AutorHasindu Gamaarachchi
AutorAndre Sim
AutorHarshil Patel
AutorHwee Meng Low
AutorChristopher Hendra
AutorLaura Wratten
AutorChristopher Hakkaart
AutorChelsea Sawyer
AutorViktoriia Iakovleva
AutorPuay Leng Lee
AutorLixia Xin
AutorHui En Vanessa Ng
AutorJia Min Loo
AutorXuewen Ong
AutorHui Qi Amanda Ng
AutorJiaxu Wang
AutorWei Qian Casslynn Koh
AutorSuk Yeah Polly Poon
AutorDominik Stanojevic
AutorHoang-Dai Tran
AutorKok Hao Edwin Lim
AutorShen Yon Toh
AutorPhilip Andrew Ewels
AutorHuck-Hui Ng
AutorN. Gopalakrishna Iyer
AutorAlexandre Thiery
AutorWee Joo Chng
AutorLeilei Chen
AutorRamanuj DasGupta
AutorMile Sikic
AutorYun-Shen Chan
AutorBoon Ooi Patrick Tan
AutorYue Wan
AutorWai Leong Tam
AutorQiang Yu
AutorChiea Chuan Khor
AutorTorsten Wüstefeld
AutorAlexander Lezhava
AutorPloy N. Pratanwanich
AutorMichael I. Love
AutorWee Siong Sho Goh
AutorSarah B. Ng
AutorAlicia Oshlack
AutorN. Gopalakrishna Iyer
AutorQiang Yu
AutorJonathan Göke
Autorova ustanovaSveučilište u Zagrebu
Fakultet elektrotehnike i računarstva
(Zavod za elektroničke sustave i obradbu informacija)
Znanstveno / umjetničko
područje, polje i grana		TEHNIČKE ZNANOSTI
Interdisciplinarne tehničke znanosti
Sažetak (engleski)
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... Više 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. Sakrij dio sažetka
Ključne riječi (engleski)
Jezikengleski
Vrsta publikacijeZnanstveni rad - Izvorni znanstveni rad
Status objaveObjavljen
Vrsta recenzijeRecenziran - međunarodna recenzija
Verzija publikacijeObjavljena verzija rada (izdavačev PDF)
Naslov časopisaNature methods
Brojčani podacivol. -, br. -, str. -, -
p-ISSN1548-7091
e-ISSN1548-7105
DOIhttps://doi.org/10.1101/2021.04.21.440736
URN:NBNurn:nbn:hr:168:644152
Datum objave publikacije2025
Vrsta resursaTekst
Prava pristupaOtvoreni pristup
Uvjeti korištenjaIkona licence Imenovanje 4.0 međunarodna (CC BY 4.0)
Datum i vrijeme pohrane2025-03-25 12:41:21
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