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HPG pore: an efficient and scalable framework for nanopore sequencing data

BACKGROUND: The use of nanopore technologies is expected to spread in the future because they are portable and can sequence long fragments of DNA molecules without prior amplification. The first nanopore sequencer available, the MinION™ from Oxford Nanopore Technologies, is a USB-connected, portable...

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Autores principales: Tarraga, Joaquin, Gallego, Asunción, Arnau, Vicente, Medina, Ignacio, Dopazo, Joaquin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4769497/
https://www.ncbi.nlm.nih.gov/pubmed/26921234
http://dx.doi.org/10.1186/s12859-016-0966-0
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author Tarraga, Joaquin
Gallego, Asunción
Arnau, Vicente
Medina, Ignacio
Dopazo, Joaquin
author_facet Tarraga, Joaquin
Gallego, Asunción
Arnau, Vicente
Medina, Ignacio
Dopazo, Joaquin
author_sort Tarraga, Joaquin
collection PubMed
description BACKGROUND: The use of nanopore technologies is expected to spread in the future because they are portable and can sequence long fragments of DNA molecules without prior amplification. The first nanopore sequencer available, the MinION™ from Oxford Nanopore Technologies, is a USB-connected, portable device that allows real-time DNA analysis. In addition, other new instruments are expected to be released soon, which promise to outperform the current short-read technologies in terms of throughput. Despite the flood of data expected from this technology, the data analysis solutions currently available are only designed to manage small projects and are not scalable. RESULTS: Here we present HPG Pore, a toolkit for exploring and analysing nanopore sequencing data. HPG Pore can run on both individual computers and in the Hadoop distributed computing framework, which allows easy scale-up to manage the large amounts of data expected to result from extensive use of nanopore technologies in the future. CONCLUSIONS: HPG Pore allows for virtually unlimited sequencing data scalability, thus guaranteeing its continued management in near future scenarios. HPG Pore is available in GitHub at http://github.com/opencb/hpg-pore.
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spelling pubmed-47694972016-02-28 HPG pore: an efficient and scalable framework for nanopore sequencing data Tarraga, Joaquin Gallego, Asunción Arnau, Vicente Medina, Ignacio Dopazo, Joaquin BMC Bioinformatics Software BACKGROUND: The use of nanopore technologies is expected to spread in the future because they are portable and can sequence long fragments of DNA molecules without prior amplification. The first nanopore sequencer available, the MinION™ from Oxford Nanopore Technologies, is a USB-connected, portable device that allows real-time DNA analysis. In addition, other new instruments are expected to be released soon, which promise to outperform the current short-read technologies in terms of throughput. Despite the flood of data expected from this technology, the data analysis solutions currently available are only designed to manage small projects and are not scalable. RESULTS: Here we present HPG Pore, a toolkit for exploring and analysing nanopore sequencing data. HPG Pore can run on both individual computers and in the Hadoop distributed computing framework, which allows easy scale-up to manage the large amounts of data expected to result from extensive use of nanopore technologies in the future. CONCLUSIONS: HPG Pore allows for virtually unlimited sequencing data scalability, thus guaranteeing its continued management in near future scenarios. HPG Pore is available in GitHub at http://github.com/opencb/hpg-pore. BioMed Central 2016-02-27 /pmc/articles/PMC4769497/ /pubmed/26921234 http://dx.doi.org/10.1186/s12859-016-0966-0 Text en © Tarraga et al. 2016 Open AccessThis 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
Tarraga, Joaquin
Gallego, Asunción
Arnau, Vicente
Medina, Ignacio
Dopazo, Joaquin
HPG pore: an efficient and scalable framework for nanopore sequencing data
title HPG pore: an efficient and scalable framework for nanopore sequencing data
title_full HPG pore: an efficient and scalable framework for nanopore sequencing data
title_fullStr HPG pore: an efficient and scalable framework for nanopore sequencing data
title_full_unstemmed HPG pore: an efficient and scalable framework for nanopore sequencing data
title_short HPG pore: an efficient and scalable framework for nanopore sequencing data
title_sort hpg pore: an efficient and scalable framework for nanopore sequencing data
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4769497/
https://www.ncbi.nlm.nih.gov/pubmed/26921234
http://dx.doi.org/10.1186/s12859-016-0966-0
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