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2024
Pardo-Palacios, Francisco J.; Wang, Dingjie; Reese, Fairlie; Diekhans, Mark; Carbonell-Sala, Sílvia; Williams, Brian; Loveland, Jane E.; María, Maite De; Adams, Matthew S.; Balderrama-Gutierrez, Gabriela; Behera, Amit K.; Martinez, Jose M. Gonzalez; Hunt, Toby; Lagarde, Julien; Liang, Cindy E.; Li, Haoran; Meade, Marcus Jerryd; Amador, David A. Moraga; Prjibelski, Andrey D.; Birol, Inanc; Bostan, Hamed; Brooks, Ashley M.; Çelik, Muhammed Hasan; Chen, Ying; Du, Mei R. M.; Felton, Colette; Göke, Jonathan; Hafezqorani, Saber; Herwig, Ralf; Kawaji, Hideya; Lee, Joseph; Li, Jian-Liang; Lienhard, Matthias; 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 E.; Capella-Gutierrez, Salvador; Cousineau, Alyssa; Dhillon, Namrita; Fernandez-Gonzalez, Jose M.; Ferrández-Peral, Luis; Garcia-Reyero, Natàlia; Götz, 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; Ren, Xingjie; Rouchka, Eric; Saint-John, Brandon; Sapena, Enrique; Sheynkman, Leon; Smith, Melissa Laird; Suner, Marie-Marthe; Takahashi, Hazuki; Youngworth, Ingrid A.; Carninci, Piero; Denslow, Nancy D.; Guigó, Roderic; Hunter, Margaret E.; Maehr, Rene; Shen, Yin; Tilgner, Hagen U.; Wold, Barbara J.; Vollmers, Christopher; Frankish, Adam; Au, Kin Fai; Sheynkman, Gloria M.; Mortazavi, Ali; Conesa, Ana; Brooks, Angela N.
Systematic assessment of long-read RNA-seq methods for transcript identification and quantification Journal Article
In: Nat Methods, 2024, ISSN: 1548-7105.
@article{Pardo-Palacios2024,
title = {Systematic assessment of long-read RNA-seq methods for transcript identification and quantification},
author = {Francisco J. Pardo-Palacios and Dingjie Wang and Fairlie Reese and Mark Diekhans and Sílvia Carbonell-Sala and Brian Williams and Jane E. Loveland and Maite De María and Matthew S. Adams and Gabriela Balderrama-Gutierrez and Amit K. Behera and Jose M. Gonzalez Martinez and Toby Hunt and Julien Lagarde and Cindy E. Liang and Haoran Li and Marcus Jerryd Meade and David A. Moraga Amador and Andrey D. Prjibelski and Inanc Birol and Hamed Bostan and Ashley M. Brooks and Muhammed Hasan Çelik and Ying Chen and Mei R. M. Du and Colette Felton and Jonathan Göke and Saber Hafezqorani and Ralf Herwig and Hideya Kawaji and Joseph Lee and Jian-Liang Li and Matthias Lienhard and Alla Mikheenko and Dennis Mulligan and Ka Ming Nip and Mihaela Pertea and Matthew E. Ritchie and Andre D. Sim and Alison D. Tang and Yuk Kei Wan and Changqing Wang and Brandon Y. Wong and Chen Yang and If Barnes and Andrew E. Berry and Salvador Capella-Gutierrez and Alyssa Cousineau and Namrita Dhillon and Jose M. Fernandez-Gonzalez and Luis Ferrández-Peral and Natàlia Garcia-Reyero and Stefan Götz and Carles Hernández-Ferrer and Liudmyla Kondratova and Tianyuan Liu and Alessandra Martinez-Martin and Carlos Menor and Jorge Mestre-Tomás and Jonathan M. Mudge and Nedka G. Panayotova and Alejandro Paniagua and Dmitry Repchevsky and Xingjie Ren and Eric Rouchka and Brandon Saint-John and Enrique Sapena and Leon Sheynkman and Melissa Laird Smith and Marie-Marthe Suner and Hazuki Takahashi and Ingrid A. Youngworth and Piero Carninci and Nancy D. Denslow and Roderic Guigó and Margaret E. Hunter and Rene Maehr and Yin Shen and Hagen U. Tilgner and Barbara J. Wold and Christopher Vollmers and Adam Frankish and Kin Fai Au and Gloria M. Sheynkman and Ali Mortazavi and Ana Conesa and Angela N. Brooks},
doi = {10.1038/s41592-024-02298-3},
issn = {1548-7105},
year = {2024},
date = {2024-06-07},
urldate = {2024-06-07},
journal = {Nat Methods},
publisher = {Springer Science and Business Media LLC},
abstract = {<jats:title>Abstract</jats:title><jats:p>The Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. Using different protocols and sequencing platforms, the consortium generated over 427 million long-read sequences from complementary DNA and direct RNA datasets, encompassing human, mouse and manatee species. Developers utilized these data to address challenges in transcript isoform detection, quantification and de novo transcript detection. 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. Incorporating additional orthogonal data and replicate samples is advised when aiming to detect rare and novel transcripts or using reference-free approaches. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.</jats:p>},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Pardo-Palacios, Francisco J.; Arzalluz-Luque, Angeles; Kondratova, Liudmyla; Salguero, Pedro; Mestre-Tomás, Jorge; Amorín, Rocío; Estevan-Morió, Eva; Liu, Tianyuan; Nanni, Adalena; McIntyre, Lauren; Tseng, Elizabeth; Conesa, Ana
SQANTI3: curation of long-read transcriptomes for accurate identification of known and novel isoforms Journal Article
In: Nat Methods, vol. 21, no. 5, pp. 793–797, 2024, ISSN: 1548-7105.
@article{Pardo-Palacios2024b,
title = {SQANTI3: curation of long-read transcriptomes for accurate identification of known and novel isoforms},
author = {Francisco J. Pardo-Palacios and Angeles Arzalluz-Luque and Liudmyla Kondratova and Pedro Salguero and Jorge Mestre-Tomás and Rocío Amorín and Eva Estevan-Morió and Tianyuan Liu and Adalena Nanni and Lauren McIntyre and Elizabeth Tseng and Ana Conesa},
doi = {10.1038/s41592-024-02229-2},
issn = {1548-7105},
year = {2024},
date = {2024-05-00},
urldate = {2024-05-00},
journal = {Nat Methods},
volume = {21},
number = {5},
pages = {793--797},
publisher = {Springer Science and Business Media LLC},
abstract = {<jats:title>Abstract</jats:title><jats:p>SQANTI3 is a tool designed for the quality control, curation and annotation of long-read transcript models obtained with third-generation sequencing technologies. Leveraging its annotation framework, SQANTI3 calculates quality descriptors of transcript models, junctions and transcript ends. With this information, potential artifacts can be identified and replaced with reliable sequences. Furthermore, the integrated functional annotation feature enables subsequent functional iso-transcriptomics analyses.</jats:p>},
keywords = {},
pubstate = {published},
tppubtype = {article}
}