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GReEn: a tool for efficient compression of genome resequencing data

Research in the genomic sciences is confronted with the volume of sequencing and resequencing data increasing at a higher pace than that of data storage and communication resources, shifting a significant part of research budgets from the sequencing component of a project to the computational one. H...

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Detalles Bibliográficos
Autores principales: Pinho, Armando J., Pratas, Diogo, Garcia, Sara P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287168/
https://www.ncbi.nlm.nih.gov/pubmed/22139935
http://dx.doi.org/10.1093/nar/gkr1124
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author Pinho, Armando J.
Pratas, Diogo
Garcia, Sara P.
author_facet Pinho, Armando J.
Pratas, Diogo
Garcia, Sara P.
author_sort Pinho, Armando J.
collection PubMed
description Research in the genomic sciences is confronted with the volume of sequencing and resequencing data increasing at a higher pace than that of data storage and communication resources, shifting a significant part of research budgets from the sequencing component of a project to the computational one. Hence, being able to efficiently store sequencing and resequencing data is a problem of paramount importance. In this article, we describe GReEn (Genome Resequencing Encoding), a tool for compressing genome resequencing data using a reference genome sequence. It overcomes some drawbacks of the recently proposed tool GRS, namely, the possibility of compressing sequences that cannot be handled by GRS, faster running times and compression gains of over 100-fold for some sequences. This tool is freely available for non-commercial use at ftp://ftp.ieeta.pt/∼ap/codecs/GReEn1.tar.gz.
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spelling pubmed-32871682012-02-27 GReEn: a tool for efficient compression of genome resequencing data Pinho, Armando J. Pratas, Diogo Garcia, Sara P. Nucleic Acids Res Methods Online Research in the genomic sciences is confronted with the volume of sequencing and resequencing data increasing at a higher pace than that of data storage and communication resources, shifting a significant part of research budgets from the sequencing component of a project to the computational one. Hence, being able to efficiently store sequencing and resequencing data is a problem of paramount importance. In this article, we describe GReEn (Genome Resequencing Encoding), a tool for compressing genome resequencing data using a reference genome sequence. It overcomes some drawbacks of the recently proposed tool GRS, namely, the possibility of compressing sequences that cannot be handled by GRS, faster running times and compression gains of over 100-fold for some sequences. This tool is freely available for non-commercial use at ftp://ftp.ieeta.pt/∼ap/codecs/GReEn1.tar.gz. Oxford University Press 2012-02 2011-12-01 /pmc/articles/PMC3287168/ /pubmed/22139935 http://dx.doi.org/10.1093/nar/gkr1124 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods Online
Pinho, Armando J.
Pratas, Diogo
Garcia, Sara P.
GReEn: a tool for efficient compression of genome resequencing data
title GReEn: a tool for efficient compression of genome resequencing data
title_full GReEn: a tool for efficient compression of genome resequencing data
title_fullStr GReEn: a tool for efficient compression of genome resequencing data
title_full_unstemmed GReEn: a tool for efficient compression of genome resequencing data
title_short GReEn: a tool for efficient compression of genome resequencing data
title_sort green: a tool for efficient compression of genome resequencing data
topic Methods Online
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287168/
https://www.ncbi.nlm.nih.gov/pubmed/22139935
http://dx.doi.org/10.1093/nar/gkr1124
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