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BMC Bioinformatics. 2016 Feb 27;17:107. doi: 10.1186/s12859-016-0966-0.

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

Author information

1
Computational Genomics Department, Centro de Investigación Príncipe Felipe (CIPF), Valencia, 46012, Spain. jtarraga@cipf.es.
2
Computational Genomics Department, Centro de Investigación Príncipe Felipe (CIPF), Valencia, 46012, Spain. agallego@cipf.es.
3
Departamento de Informática, ETSE, Universidad de Valencia, Valencia, Spain. Vicente.Arnau@uv.es.
4
HPC Service, University Information Services, University of Cambridge, Cambridge, UK. im411@cam.ac.uk.
5
Computational Genomics Department, Centro de Investigación Príncipe Felipe (CIPF), Valencia, 46012, Spain. jdopazo@cipf.es.
6
Bioinformatics of Rare Diseases (BIER), CIBER de Enfermedades Raras (CIBERER), Valencia, Spain. jdopazo@cipf.es.
7
Functional Genomics Node, (INB) at CIPF, Valencia, 46012, Spain. jdopazo@cipf.es.

Abstract

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.

PMID:
26921234
PMCID:
PMC4769497
DOI:
10.1186/s12859-016-0966-0
[Indexed for MEDLINE]
Free PMC Article

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