Long-TREC: The Long-Reads Transcriptomics European Consortium. The next generation transcriptome biology revealed by single molecule sequencing technologies

Informazioni relative al progetto

LongTREC

ID dell’accordo di sovvenzione: 101072892

DOI

10.3030/101072892

Data della firma CE 14 Luglio 2022

Data di avvio 1 Ottobre 2022

Data di completamento 30 Settembre 2026

Finanziato da

• Marie Skłodowska-Curie Actions (MSCA)

Costo totale

Nessun dato

Contributo UE

€ 2 621 931,00

Coordinato da

AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS
Spain

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Documents, reports (9)

Interim report including links to a protocol repository

Updated report on the state of library preparation, sequencing and mapping algorithm developments, including links to a protocol repository (i.e. protocols.io) and GitHub for code of novel mapping algorithms

Interim report on the state of algorithm developments in WP4 applied to use cases

Updated progress report on the state of algorithm developments in WP4, including a list of links to GitHub repositories containing code

Initial report on the state of algorithm developments in WP5
Interim report on the state of algorithm developed in WP5 and pipelines comparison

Updated progress report on the state of algorithm developments in WP5 and comparison of pipelines

Initial progress report on the state of algorithm developments in WP3

Progress report on the state of algorithm developments in WP3

Progress report on the state of library preparation, sequencing and mapping algorithm

Progress report on the state of library preparation, sequencing, and mapping algorithm developments.

Interim report on the state of algorithm developed in WP3, including benchmarks

Updated progress report on the state of algorithm developments in WP3, including a list of links to a GitHub repository containing code

Progress report on the state of algorithm developments in WP4
LongTREC website and social network profiles

Pubblicazioni

Peer reviewed articles (6)

IsoTools 2.0: Software for Comprehensive Analysis of Long-read Transcriptome Sequencing Data

Autori: Yalan Bi, Tom Lukas Lankenau, Matthias Lienhard, Ralf Herwig
Pubblicato in: Journal of Molecular Biology, 2025, ISSN 0022-2836
Editore: Elsevier BV
DOI: 10.1016/j.jmb.2025.169049

Icarust, a real-time simulator for Oxford Nanopore adaptive sampling

Autori: Rory Munro, Satrio Wibowo, Alexander Payne, Matthew Loose
Pubblicato in: Bioinformatics, Numero 40, 2024, ISSN 1367-4811
Editore: Oxford University Press (OUP)
DOI: 10.1093/bioinformatics/btae141

Long-read transcriptome sequencing of CLL and MDS patients uncovers molecular effects of<i>SF3B1</i>mutations

Autori: Alicja Pacholewska, Matthias Lienhard, Mirko Brüggemann, Heike Hänel, Lorina Bilalli, Anja Königs, Felix Heß, Kerstin Becker, Karl Köhrer, Jesko Kaiser, Holger Gohlke, Norbert Gattermann, Michael Hallek, Carmen D. Herling, Julian König, Christina Grimm, Ralf Herwig, Kathi Zarnack, Michal R. Schweiger
Pubblicato in: Genome Research, Numero 34, 2024, ISSN 1088-9051
Editore: Cold Spring Harbor Laboratory
DOI: 10.1101/GR.279327.124

Evidence-based unification of potato gene models with the UniTato collaborative genome browser

Autori: Maja Zagorščak, Jan Zrimec, Carissa Bleker, Nadja Nolte, Mojca Juteršek, Živa Ramšak, Kristina Gruden, Marko Petek
Pubblicato in: Frontiers in Plant Science, Numero 15, 2024, ISSN 1664-462X
Editore: Frontiers Media SA
DOI: 10.3389/FPLS.2024.1352253

Toward the use of nanopore RNA sequencing technologies in the clinic: challenges and opportunities

Autori: Xanthi-Lida Katopodi, Oguzhan Begik, Eva Maria Novoa
Pubblicato in: Nucleic Acids Research, Numero 53, 2025, ISSN 0305-1048
Editore: Oxford University Press (OUP)
DOI: 10.1093/NAR/GKAF128

Profiling the epigenome using long-read sequencing

Autori: Tianyuan Liu, Ana Conesa
Pubblicato in: Nature Genetics, Numero 57, 2025, ISSN 1061-4036
Editore: Springer Science and Business Media LLC
DOI: 10.1038/s41588-024-02038-5