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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...

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Autores principales: Nazzari, Marta, Hauser, Duncan, van Herwijnen, Marcel, Romitti, Mírian, Carvalho, Daniel J, Kip, Anna M, Caiment, Florian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
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.
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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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