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Computational Methods for Mapping, Assembly and Quantification for Coding and Non-coding Transcripts

The measurement of gene expression has long provided significant insight into biological functions. The development of high-throughput short-read sequencing technology has revealed transcriptional complexity at an unprecedented scale, and informed almost all areas of biology. However, as researchers...

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Detalles Bibliográficos
Autores principales: Babarinde, Isaac A., Li, Yuhao, Hutchins, Andrew P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6526290/
https://www.ncbi.nlm.nih.gov/pubmed/31193391
http://dx.doi.org/10.1016/j.csbj.2019.04.012
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author Babarinde, Isaac A.
Li, Yuhao
Hutchins, Andrew P.
author_facet Babarinde, Isaac A.
Li, Yuhao
Hutchins, Andrew P.
author_sort Babarinde, Isaac A.
collection PubMed
description The measurement of gene expression has long provided significant insight into biological functions. The development of high-throughput short-read sequencing technology has revealed transcriptional complexity at an unprecedented scale, and informed almost all areas of biology. However, as researchers have sought to gather more insights from the data, these new technologies have also increased the computational analysis burden. In this review, we describe typical computational pipelines for RNA-Seq analysis and discuss their strengths and weaknesses for the assembly, quantification and analysis of coding and non-coding RNAs. We also discuss the assembly of transposable elements into transcripts, and the difficulty these repetitive elements pose. In summary, RNA-Seq is a powerful technology that is likely to remain a key asset in the biologist's toolkit.
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spelling pubmed-65262902019-05-28 Computational Methods for Mapping, Assembly and Quantification for Coding and Non-coding Transcripts Babarinde, Isaac A. Li, Yuhao Hutchins, Andrew P. Comput Struct Biotechnol J Review Article The measurement of gene expression has long provided significant insight into biological functions. The development of high-throughput short-read sequencing technology has revealed transcriptional complexity at an unprecedented scale, and informed almost all areas of biology. However, as researchers have sought to gather more insights from the data, these new technologies have also increased the computational analysis burden. In this review, we describe typical computational pipelines for RNA-Seq analysis and discuss their strengths and weaknesses for the assembly, quantification and analysis of coding and non-coding RNAs. We also discuss the assembly of transposable elements into transcripts, and the difficulty these repetitive elements pose. In summary, RNA-Seq is a powerful technology that is likely to remain a key asset in the biologist's toolkit. Research Network of Computational and Structural Biotechnology 2019-05-07 /pmc/articles/PMC6526290/ /pubmed/31193391 http://dx.doi.org/10.1016/j.csbj.2019.04.012 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review Article
Babarinde, Isaac A.
Li, Yuhao
Hutchins, Andrew P.
Computational Methods for Mapping, Assembly and Quantification for Coding and Non-coding Transcripts
title Computational Methods for Mapping, Assembly and Quantification for Coding and Non-coding Transcripts
title_full Computational Methods for Mapping, Assembly and Quantification for Coding and Non-coding Transcripts
title_fullStr Computational Methods for Mapping, Assembly and Quantification for Coding and Non-coding Transcripts
title_full_unstemmed Computational Methods for Mapping, Assembly and Quantification for Coding and Non-coding Transcripts
title_short Computational Methods for Mapping, Assembly and Quantification for Coding and Non-coding Transcripts
title_sort computational methods for mapping, assembly and quantification for coding and non-coding transcripts
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6526290/
https://www.ncbi.nlm.nih.gov/pubmed/31193391
http://dx.doi.org/10.1016/j.csbj.2019.04.012
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