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CODA: a combo-Seq data analysis workflow
The analysis of the combined mRNA and miRNA content of a biological sample can be of interest for answering several research questions, like biomarkers discovery, or mRNA–miRNA interactions. However, the process is costly and time-consuming, separate libraries need to be prepared and sequenced on di...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9851309/ https://www.ncbi.nlm.nih.gov/pubmed/36545800 http://dx.doi.org/10.1093/bib/bbac582 |
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author | Nazzari, Marta Hauser, Duncan van Herwijnen, Marcel Romitti, Mírian Carvalho, Daniel J Kip, Anna M Caiment, Florian |
author_facet | Nazzari, Marta Hauser, Duncan van Herwijnen, Marcel Romitti, Mírian Carvalho, Daniel J Kip, Anna M Caiment, Florian |
author_sort | Nazzari, Marta |
collection | PubMed |
description | The analysis of the combined mRNA and miRNA content of a biological sample can be of interest for answering several research questions, like biomarkers discovery, or mRNA–miRNA interactions. However, the process is costly and time-consuming, separate libraries need to be prepared and sequenced on different flowcells. Combo-Seq is a library prep kit that allows us to prepare combined mRNA–miRNA libraries starting from very low total RNA. To date, no dedicated bioinformatics method exists for the processing of Combo-Seq data. In this paper, we describe CODA (Combo-seq Data Analysis), a workflow specifically developed for the processing of Combo-Seq data that employs existing free-to-use tools. We compare CODA with exceRpt, the pipeline suggested by the kit manufacturer for this purpose. We also evaluate how Combo-Seq libraries analysed with CODA perform compared with conventional poly(A) and small RNA libraries prepared from the same samples. We show that using CODA more successfully trimmed reads are recovered compared with exceRpt, and the difference is more dramatic with short sequencing reads. We demonstrate how Combo-Seq identifies as many genes and fewer miRNAs compared to the standard libraries, and how miRNA validation favours conventional small RNA libraries over Combo-Seq. The CODA code is available at https://github.com/marta-nazzari/CODA. |
format | Online Article Text |
id | pubmed-9851309 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-98513092023-01-20 CODA: a combo-Seq data analysis workflow Nazzari, Marta Hauser, Duncan van Herwijnen, Marcel Romitti, Mírian Carvalho, Daniel J Kip, Anna M Caiment, Florian Brief Bioinform Problem Solving Protocol The analysis of the combined mRNA and miRNA content of a biological sample can be of interest for answering several research questions, like biomarkers discovery, or mRNA–miRNA interactions. However, the process is costly and time-consuming, separate libraries need to be prepared and sequenced on different flowcells. Combo-Seq is a library prep kit that allows us to prepare combined mRNA–miRNA libraries starting from very low total RNA. To date, no dedicated bioinformatics method exists for the processing of Combo-Seq data. In this paper, we describe CODA (Combo-seq Data Analysis), a workflow specifically developed for the processing of Combo-Seq data that employs existing free-to-use tools. We compare CODA with exceRpt, the pipeline suggested by the kit manufacturer for this purpose. We also evaluate how Combo-Seq libraries analysed with CODA perform compared with conventional poly(A) and small RNA libraries prepared from the same samples. We show that using CODA more successfully trimmed reads are recovered compared with exceRpt, and the difference is more dramatic with short sequencing reads. We demonstrate how Combo-Seq identifies as many genes and fewer miRNAs compared to the standard libraries, and how miRNA validation favours conventional small RNA libraries over Combo-Seq. The CODA code is available at https://github.com/marta-nazzari/CODA. Oxford University Press 2022-12-21 /pmc/articles/PMC9851309/ /pubmed/36545800 http://dx.doi.org/10.1093/bib/bbac582 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Problem Solving Protocol Nazzari, Marta Hauser, Duncan van Herwijnen, Marcel Romitti, Mírian Carvalho, Daniel J Kip, Anna M Caiment, Florian CODA: a combo-Seq data analysis workflow |
title | CODA: a combo-Seq data analysis workflow |
title_full | CODA: a combo-Seq data analysis workflow |
title_fullStr | CODA: a combo-Seq data analysis workflow |
title_full_unstemmed | CODA: a combo-Seq data analysis workflow |
title_short | CODA: a combo-Seq data analysis workflow |
title_sort | coda: a combo-seq data analysis workflow |
topic | Problem Solving Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9851309/ https://www.ncbi.nlm.nih.gov/pubmed/36545800 http://dx.doi.org/10.1093/bib/bbac582 |
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