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CARGO: effective format-free compressed storage of genomic information

The recent super-exponential growth in the amount of sequencing data generated worldwide has put techniques for compressed storage into the focus. Most available solutions, however, are strictly tied to specific bioinformatics formats, sometimes inheriting from them suboptimal design choices; this h...

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Detalles Bibliográficos
Autores principales: Roguski, Łukasz, Ribeca, Paolo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937321/
https://www.ncbi.nlm.nih.gov/pubmed/27131376
http://dx.doi.org/10.1093/nar/gkw318
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author Roguski, Łukasz
Ribeca, Paolo
author_facet Roguski, Łukasz
Ribeca, Paolo
author_sort Roguski, Łukasz
collection PubMed
description The recent super-exponential growth in the amount of sequencing data generated worldwide has put techniques for compressed storage into the focus. Most available solutions, however, are strictly tied to specific bioinformatics formats, sometimes inheriting from them suboptimal design choices; this hinders flexible and effective data sharing. Here, we present CARGO (Compressed ARchiving for GenOmics), a high-level framework to automatically generate software systems optimized for the compressed storage of arbitrary types of large genomic data collections. Straightforward applications of our approach to FASTQ and SAM archives require a few lines of code, produce solutions that match and sometimes outperform specialized format-tailored compressors and scale well to multi-TB datasets. All CARGO software components can be freely downloaded for academic and non-commercial use from http://bio-cargo.sourceforge.net.
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spelling pubmed-49373212016-07-11 CARGO: effective format-free compressed storage of genomic information Roguski, Łukasz Ribeca, Paolo Nucleic Acids Res Methods Online The recent super-exponential growth in the amount of sequencing data generated worldwide has put techniques for compressed storage into the focus. Most available solutions, however, are strictly tied to specific bioinformatics formats, sometimes inheriting from them suboptimal design choices; this hinders flexible and effective data sharing. Here, we present CARGO (Compressed ARchiving for GenOmics), a high-level framework to automatically generate software systems optimized for the compressed storage of arbitrary types of large genomic data collections. Straightforward applications of our approach to FASTQ and SAM archives require a few lines of code, produce solutions that match and sometimes outperform specialized format-tailored compressors and scale well to multi-TB datasets. All CARGO software components can be freely downloaded for academic and non-commercial use from http://bio-cargo.sourceforge.net. Oxford University Press 2016-07-08 2016-04-29 /pmc/articles/PMC4937321/ /pubmed/27131376 http://dx.doi.org/10.1093/nar/gkw318 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods Online
Roguski, Łukasz
Ribeca, Paolo
CARGO: effective format-free compressed storage of genomic information
title CARGO: effective format-free compressed storage of genomic information
title_full CARGO: effective format-free compressed storage of genomic information
title_fullStr CARGO: effective format-free compressed storage of genomic information
title_full_unstemmed CARGO: effective format-free compressed storage of genomic information
title_short CARGO: effective format-free compressed storage of genomic information
title_sort cargo: effective format-free compressed storage of genomic information
topic Methods Online
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937321/
https://www.ncbi.nlm.nih.gov/pubmed/27131376
http://dx.doi.org/10.1093/nar/gkw318
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