2.
Mestre-Tomás, Jorge; Liu, Tianyuan; Pardo-Palacios, Francisco; Conesa, Ana
SQANTI-SIM: a simulator of controlled transcript novelty for lrRNA-seq benchmark Journal Article
In: Genome Biol, vol. 24, no. 1, 0000, ISSN: 1474-760X.
@article{Mestre-Tomás2023,
title = {SQANTI-SIM: a simulator of controlled transcript novelty for lrRNA-seq benchmark},
author = {Jorge Mestre-Tomás and Tianyuan Liu and Francisco Pardo-Palacios and Ana Conesa},
doi = {10.1186/s13059-023-03127-0},
issn = {1474-760X},
journal = {Genome Biol},
volume = {24},
number = {1},
publisher = {Springer Science and Business Media LLC},
abstract = {Abstract Long-read RNA sequencing has emerged as a powerful tool for transcript discovery, even in well-annotated organisms. However, assessing the accuracy of different methods in identifying annotated and novel transcripts remains a challenge. Here, we present SQANTI-SIM, a versatile tool that wraps around popular long-read simulators to allow precise management of transcript novelty based on the structural categories defined by SQANTI3. By selectively excluding specific transcripts from the reference dataset, SQANTI-SIM effectively emulates scenarios involving unannotated transcripts. Furthermore, the tool provides customizable features and supports the simulation of additional types of data, representing the first multi-omics simulation tool for the lrRNA-seq field. },
keywords = {},
pubstate = {published},
tppubtype = {article}
}
1.
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, 0000, 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},
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}
}
<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>