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Sequencing of mRNA from Whole Blood using Nanopore Sequencing
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HPG pore: an efficient and scalable framework for nanopore sequencing data.

Joaquin Tarraga1, Asunción Gallego2, Vicente Arnau3

  • 1Computational Genomics Department, Centro de Investigación Príncipe Felipe (CIPF), Valencia, 46012, Spain. jtarraga@cipf.es.

BMC Bioinformatics
|February 28, 2016
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Summary

HPG Pore is a new toolkit for analyzing nanopore sequencing data. It offers scalable solutions for managing the large datasets generated by portable DNA sequencing technologies.

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Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Nanopore sequencing technology offers portable, real-time DNA analysis with long-read capabilities.
  • Emerging nanopore instruments promise higher throughput than current short-read technologies.
  • Existing data analysis tools struggle to manage the large datasets from nanopore sequencing.

Purpose of the Study:

  • To introduce HPG Pore, a novel toolkit for nanopore sequencing data analysis.
  • To provide a scalable solution for managing large-scale nanopore sequencing data.

Main Methods:

  • HPG Pore is designed to run on individual computers.
  • HPG Pore integrates with the Hadoop distributed computing framework for scalability.

Main Results:

  • HPG Pore enables the analysis and exploration of nanopore sequencing data.
  • The toolkit facilitates easy scale-up for managing extensive future data volumes.

Conclusions:

  • HPG Pore provides virtually unlimited scalability for sequencing data management.
  • This ensures continued data management for near-future scenarios.
  • HPG Pore is publicly available on GitHub.