De Novo DNA assembler for third generation sequencers’ reads based on BLASR algorithm

Michał Winiarski , Wiktor Kuśmirek , Robert Marek Nowak

Abstract

The most significant differences between second and third sequencing generation are length of reads and percentage of errors. In the field of de novo DNA assembly there is a need for new effective algorithms as these used for second generation reads are highly ineffective or even unusable when applied to the successor. In this article we propose a solution tailored for DNA assembly of reads from third generation sequencers. In this approach we use overlap-layout-consensus (OLC) graph method. It is composed of number of algorithms focusing on time and memory optimization. The proposed algorithm was implemented as shared library and added as a new module to the ’dnaasm’ de novo assembler. The implementation has been tested on simulated as well as real data. Results prove increase in speed and memory consumption in comparison with other de novo DNA assemblers.
Author Michał Winiarski (FEIT / ICS)
Michał Winiarski,,
- The Institute of Computer Science
, Wiktor Kuśmirek (FEIT / IN)
Wiktor Kuśmirek,,
- The Institute of Computer Science
, Robert Marek Nowak (FEIT / IN)
Robert Marek Nowak,,
- The Institute of Computer Science
Pages108083C-1-108083C-9
Publication size in sheets0.5
Book Romaniuk Ryszard, Linczuk Maciej Grzegorz (eds.): Proceedings of SPIE: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2018, vol. 10808, 2018, SPIE - the International Society for Optics and Photonics, ISBN 9781510622036, 2086 p.
Keywords in EnglishDNA assembler, de novo assembling, third-generation sequencing, computer program, overlap consensus graph
DOIDOI:10.1117/12.2501542
URL https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10808/2501542/De-Novo-DNA-assembler-for-third-generation-sequencers-reads-based/10.1117/12.2501542.full?SSO=1
Languageen angielski
File
108083C_kusmirek.pdf 797.24 KB
Score (nominal)15
ScoreMinisterial score = 15.0, 16-10-2018, BookChapterMatConf
Ministerial score (2013-2016) = 15.0, 16-10-2018, BookChapterMatConf
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