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  Systematic assessment of long-read RNA-seq methods for transcript identification and quantification

Pardo-Palacios, F. J., Wang, D., Reese, F., Diekhans, M., Carbonell-Sala, S., Williams, B., et al. (2023). Systematic assessment of long-read RNA-seq methods for transcript identification and quantification. bioRxiv, 2023.07.25.550582. doi:10.1101/2023.07.25.550582.

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2023.07.25.550582v1.full.pdf (Preprint), 25MB
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2023.07.25.550582v1.full.pdf
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Pardo-Palacios, F. J., Author
Wang, D., Author
Reese, F., Author
Diekhans, M., Author
Carbonell-Sala, S., Author
Williams, B., Author
Loveland, J. E., Author
De Maria, M., Author
Adams, M. S., Author
Balderrama-Gutierrez, G., Author
Behera, A. K., Author
Gonzalez, J. M., Author
Hunt, T., Author
Lagarde, J., Author
Liang, C. E., Author
Li, H., Author
Jerryd Meade, M., Author
Moraga Amador, D. A., Author
Prjibelski, A. D., Author
Birol, I., Author
Bostan, H., AuthorBrooks, A. M., AuthorHasan Celik, M., AuthorChen, Y., AuthorDu, M. R. M., AuthorFelton, C., AuthorGoke, J., AuthorHafezqorani, S., AuthorHerwig, R.1, Author                 Kawaji, H., AuthorLee, J., AuthorLiang Li, J., AuthorLienhard, M.1, Author                 Mikheenko, A., AuthorMulligan, D., AuthorMing Nip, K., AuthorPertea, M., AuthorRitchie, M. E., AuthorSim, A. D., AuthorTang, A. D., AuthorKei Wan, Y., AuthorWang, C., AuthorWong, B. Y., AuthorYang, C., AuthorBarnes, I., AuthorBerry, A., AuthorCapella, S., AuthorDhillon, N., AuthorFernandez-Gonzalez, J. M., AuthorFerrandez-Peral, L., AuthorGarcia-Reyero, N., AuthorGoetz, S., AuthorHernandez-Ferrer, C., AuthorKondratova, L., AuthorLiu, T., AuthorMartinez-Martin, A., AuthorMenor, C., AuthorMestre-Tomas, J., AuthorMudge, J. M., AuthorPanayotova, N. G., AuthorPaniagua, A., AuthorRepchevsky, D., AuthorRouchka, E., AuthorSaint-John, B., AuthorSapena, E., AuthorSheynkman, L., AuthorLaird Smith, M., AuthorSuner, M. M., AuthorTakahashi, H., AuthorYoungworth, I. A., AuthorCarninci, P., AuthorDenslow, N. D., AuthorGuigo, R., AuthorHunter, M. E., AuthorTilgner, H. U., AuthorWold, B. J., AuthorVollmers, C., AuthorFrankish, A., AuthorFai Au, K., AuthorSheynkman, G. M., AuthorMortazavi, A., AuthorConesa, A., AuthorBrooks, A. N., Author more..
Affiliations:
1Bioinformatics (Ralf Herwig), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_2385701              

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 Abstract: The Long-read RNA-Seq Genome Annotation Assessment Project (LRGASP) Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. The consortium generated over 427 million long-read sequences from cDNA and direct RNA datasets, encompassing human, mouse, and manatee species, using different protocols and sequencing platforms. These data were utilized by developers to address challenges in transcript isoform detection and quantification, as well as de novo transcript isoform identification. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. When aiming to detect rare and novel transcripts or when using reference-free approaches, incorporating additional orthogonal data and replicate samples are advised. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

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Language(s): eng - English
 Dates: 2023-07-27
 Publication Status: Published online
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 Table of Contents: -
 Rev. Type: -
 Identifiers: PMID: 37546854
PMC: PMC10402094
DOI: 10.1101/2023.07.25.550582
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Title: bioRxiv
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Pages: - Volume / Issue: - Sequence Number: 2023.07.25.550582 Start / End Page: - Identifier: -