Systematic assessment of long-read RNA-seq methods for transcript identification and quantification
Author:
Pardo-Palacios Francisco J., Wang Dingjie, Reese Fairlie, Diekhans Mark, Carbonell-Sala Sílvia, Williams Brian, Loveland Jane E., De María Maite, Adams Matthew S., Balderrama-Gutierrez Gabriela, Behera Amit K., Gonzalez Jose M., Hunt Toby, Lagarde Julien, Liang Cindy E., Li Haoran, Meade Marcus Jerryd, Amador David A. Moraga, Prjibelski Andrey D., Birol InancORCID, Bostan Hamed, Brooks Ashley M., Çelik Muhammed Hasan, Chen Ying, Du Mei R.M., Felton Colette, Göke JonathanORCID, Hafezqorani Saber, Herwig Ralf, Kawaji Hideya, Lee Joseph, Li Jian-LiangORCID, Lienhard MatthiasORCID, Mikheenko Alla, Mulligan Dennis, Nip Ka Ming, Pertea Mihaela, Ritchie Matthew E., Sim Andre D., Tang Alison D., Wan Yuk Kei, Wang Changqing, Wong Brandon Y., Yang Chen, Barnes If, Berry Andrew, Capella SalvadorORCID, Dhillon NamritaORCID, Fernandez-Gonzalez Jose M., Ferrández-Peral Luis, Garcia-Reyero Natàlia, Goetz Stefan, Hernández-Ferrer Carles, Kondratova Liudmyla, Liu Tianyuan, Martinez-Martin Alessandra, Menor Carlos, Mestre-Tomás Jorge, Mudge Jonathan M., Panayotova Nedka G., Paniagua Alejandro, Repchevsky Dmitry, Rouchka EricORCID, Saint-John BrandonORCID, Sapena Enrique, Sheynkman Leon, Smith Melissa Laird, Suner Marie-Marthe, Takahashi HazukiORCID, Youngworth Ingrid Ashley, Carninci PieroORCID, Denslow Nancy D., Guigó Roderic, Hunter Margaret E., Tilgner Hagen U., Wold Barbara J., Vollmers Christopher, Frankish Adam, Au Kin FaiORCID, Sheynkman Gloria M., Mortazavi AliORCID, Conesa Ana, Brooks Angela N.ORCID
Abstract
AbstractThe 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 asde novotranscript 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.
Publisher
Cold Spring Harbor Laboratory
Cited by
2 articles.
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