Comparative Analysis of de Bruijn Graph Parallel Genome Assemblers

Carlos Gamboa-Venegas, Esteban Meneses

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Finding the genome of new species remains as one of the most crucial tasks in molecular biology. To achieve that end, de novo sequence assembly feeds from the vast amount of data provided by Next-Generation Sequencing technology. Therefore, genome assemblers demand a high amount of computational resources, and parallel implementations of those assemblers are readily available. This paper presents a comparison of three well-known de novo genome assemblers: Velvet, ABySS and SOAPdenovo, all of them using de Bruijn graphs and having a parallel implementation. We based our analysis on parallel execution time, scalability, quality of assembly, and sensitivity to the choice of a critical parameter (k- mer size). We found one of the tools clearly stands out for providing faster execution time and better quality in the output. Also, all assemblers are mildly sensitive to the choice of k-mer size and they all show limited scalability. We expect the findings of this paper provide a guide to the development of new algorithms and tools for scalable parallel genome sequence assemblers.

Original languageEnglish
Title of host publication2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781538675069
DOIs
StatePublished - 12 Sep 2018
Event2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - San Carlos, Costa Rica
Duration: 18 Jul 201820 Jul 2018

Publication series

Name2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings

Conference

Conference2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018
Country/TerritoryCosta Rica
CitySan Carlos
Period18/07/1820/07/18

Keywords

  • De Bruijn graph
  • De novo
  • Genome assembly
  • Parallel performance
  • Scalability

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