Highly efficient parallel approach to the next-generation DNA sequencing

  • Authors:

  • Jacek Blazewicz;Bartosz Bosak;Piotr Gawron;Marta Kasprzak;Krzysztof Kurowski;Tomasz Piontek;Aleksandra Swiercz

  • Affiliations:

  • Institute of Computing Science, Poznan University of Technology, Poznan, Poland, Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland;Poznan Supercomputing and Networking Center, Poznan, Poland;Institute of Computing Science, Poznan University of Technology, Poznan, Poland;Institute of Computing Science, Poznan University of Technology, Poznan, Poland, Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland;Poznan Supercomputing and Networking Center, Poznan, Poland;Poznan Supercomputing and Networking Center, Poznan, Poland;Institute of Computing Science, Poznan University of Technology, Poznan, Poland, Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland

  • Venue:
  • PPAM'11 Proceedings of the 9th international conference on Parallel Processing and Applied Mathematics - Volume Part II
  • Year:
  • 2011

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Abstract

Due to the rapid development of the technology, next-generation sequencers can produce huge amount of short DNA fragments covering a genomic sequence of an organism in short time. There is a need for the time-efficient algorithms which could assembly these fragments together and reconstruct the examined DNA sequence. Previously proposed algorithm for de novo assembly, SR-ASM, produced results of high quality, but required a lot of time for computations. The proposed hybrid parallel programming strategy allows one to use the two-level hierarchy: computations in threads (on a single node with many cores) and computations on different nodes in a cluster. The tests carried out on real data of Prochloroccocus marinus coming from Roche sequencer showed, that the algorithm was speeded up 20 times in comparison to the sequential approach with the maintenance of the high accuracy and beating results of other algorithms.