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Challenges in detecting and quantifying intron retention from next generation sequencing data

Intron retention (IR) occurs when an intron is transcribed into pre-mRNA and remains in the final mRNA. An increasing body of literature has demonstrated a major role for IR in numerous biological functions and in disease. Here we give an overview of the different computational approaches for detect...

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Autores principales: Broseus, Lucile, Ritchie, William
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7078297/
https://www.ncbi.nlm.nih.gov/pubmed/32206209
http://dx.doi.org/10.1016/j.csbj.2020.02.010
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author Broseus, Lucile
Ritchie, William
author_facet Broseus, Lucile
Ritchie, William
author_sort Broseus, Lucile
collection PubMed
description Intron retention (IR) occurs when an intron is transcribed into pre-mRNA and remains in the final mRNA. An increasing body of literature has demonstrated a major role for IR in numerous biological functions and in disease. Here we give an overview of the different computational approaches for detecting IR events from sequencing data. We show that these are based on different biological and computational assumptions that may lead to dramatically different results. We describe the various approaches for mitigating errors in detecting intron retention and for discovering IR signatures between different conditions.
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spelling pubmed-70782972020-03-23 Challenges in detecting and quantifying intron retention from next generation sequencing data Broseus, Lucile Ritchie, William Comput Struct Biotechnol J Review Article Intron retention (IR) occurs when an intron is transcribed into pre-mRNA and remains in the final mRNA. An increasing body of literature has demonstrated a major role for IR in numerous biological functions and in disease. Here we give an overview of the different computational approaches for detecting IR events from sequencing data. We show that these are based on different biological and computational assumptions that may lead to dramatically different results. We describe the various approaches for mitigating errors in detecting intron retention and for discovering IR signatures between different conditions. Research Network of Computational and Structural Biotechnology 2020-02-26 /pmc/articles/PMC7078297/ /pubmed/32206209 http://dx.doi.org/10.1016/j.csbj.2020.02.010 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Review Article
Broseus, Lucile
Ritchie, William
Challenges in detecting and quantifying intron retention from next generation sequencing data
title Challenges in detecting and quantifying intron retention from next generation sequencing data
title_full Challenges in detecting and quantifying intron retention from next generation sequencing data
title_fullStr Challenges in detecting and quantifying intron retention from next generation sequencing data
title_full_unstemmed Challenges in detecting and quantifying intron retention from next generation sequencing data
title_short Challenges in detecting and quantifying intron retention from next generation sequencing data
title_sort challenges in detecting and quantifying intron retention from next generation sequencing data
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7078297/
https://www.ncbi.nlm.nih.gov/pubmed/32206209
http://dx.doi.org/10.1016/j.csbj.2020.02.010
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