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A new parallel pipeline for DNA methylation analysis of long reads datasets

BACKGROUND: DNA methylation is an important mechanism of epigenetic regulation in development and disease. New generation sequencers allow genome-wide measurements of the methylation status by reading short stretches of the DNA sequence (Methyl-seq). Several software tools for methylation analysis h...

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Autores principales: Olanda, Ricardo, Pérez, Mariano, Orduña, Juan M., Tárraga, Joaquín, Dopazo, Joaquín
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5343294/
https://www.ncbi.nlm.nih.gov/pubmed/28274198
http://dx.doi.org/10.1186/s12859-017-1574-3
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author Olanda, Ricardo
Pérez, Mariano
Orduña, Juan M.
Tárraga, Joaquín
Dopazo, Joaquín
author_facet Olanda, Ricardo
Pérez, Mariano
Orduña, Juan M.
Tárraga, Joaquín
Dopazo, Joaquín
author_sort Olanda, Ricardo
collection PubMed
description BACKGROUND: DNA methylation is an important mechanism of epigenetic regulation in development and disease. New generation sequencers allow genome-wide measurements of the methylation status by reading short stretches of the DNA sequence (Methyl-seq). Several software tools for methylation analysis have been proposed over recent years. However, the current trend is that the new sequencers and the ones expected for an upcoming future yield sequences of increasing length, making these software tools inefficient and obsolete. RESULTS: In this paper, we propose a new software based on a strategy for methylation analysis of Methyl-seq sequencing data that requires much shorter execution times while yielding a better level of sensitivity, particularly for datasets composed of long reads. This strategy can be exported to other methylation, DNA and RNA analysis tools. CONCLUSIONS: The developed software tool achieves execution times one order of magnitude shorter than the existing tools, while yielding equal sensitivity for short reads and even better sensitivity for long reads. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1574-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-53432942017-03-10 A new parallel pipeline for DNA methylation analysis of long reads datasets Olanda, Ricardo Pérez, Mariano Orduña, Juan M. Tárraga, Joaquín Dopazo, Joaquín BMC Bioinformatics Software BACKGROUND: DNA methylation is an important mechanism of epigenetic regulation in development and disease. New generation sequencers allow genome-wide measurements of the methylation status by reading short stretches of the DNA sequence (Methyl-seq). Several software tools for methylation analysis have been proposed over recent years. However, the current trend is that the new sequencers and the ones expected for an upcoming future yield sequences of increasing length, making these software tools inefficient and obsolete. RESULTS: In this paper, we propose a new software based on a strategy for methylation analysis of Methyl-seq sequencing data that requires much shorter execution times while yielding a better level of sensitivity, particularly for datasets composed of long reads. This strategy can be exported to other methylation, DNA and RNA analysis tools. CONCLUSIONS: The developed software tool achieves execution times one order of magnitude shorter than the existing tools, while yielding equal sensitivity for short reads and even better sensitivity for long reads. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1574-3) contains supplementary material, which is available to authorized users. BioMed Central 2017-03-09 /pmc/articles/PMC5343294/ /pubmed/28274198 http://dx.doi.org/10.1186/s12859-017-1574-3 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Olanda, Ricardo
Pérez, Mariano
Orduña, Juan M.
Tárraga, Joaquín
Dopazo, Joaquín
A new parallel pipeline for DNA methylation analysis of long reads datasets
title A new parallel pipeline for DNA methylation analysis of long reads datasets
title_full A new parallel pipeline for DNA methylation analysis of long reads datasets
title_fullStr A new parallel pipeline for DNA methylation analysis of long reads datasets
title_full_unstemmed A new parallel pipeline for DNA methylation analysis of long reads datasets
title_short A new parallel pipeline for DNA methylation analysis of long reads datasets
title_sort new parallel pipeline for dna methylation analysis of long reads datasets
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5343294/
https://www.ncbi.nlm.nih.gov/pubmed/28274198
http://dx.doi.org/10.1186/s12859-017-1574-3
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