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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2020
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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. |
format | Online Article Text |
id | pubmed-7078297 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT broseuslucile challengesindetectingandquantifyingintronretentionfromnextgenerationsequencingdata AT ritchiewilliam challengesindetectingandquantifyingintronretentionfromnextgenerationsequencingdata |