Paired de Bruijn graphs: A novel approach for incorporating mate pair information into genome assemblers

Paul Medvedev, Son Pham, Mark Chaisson, Glenn Tesler, Pavel Pevzner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

The recent proliferation of next generation sequencing with short reads has enabled many new experimental opportunities but, at the same time, has raised formidable computational challenges in genome assembly. One of the key advances that has led to an improvement in contig lengths has been mate pairs, which facilitate the assembly of repeating regions. Mate pairs have been algorithmically incorporated into most next generation assemblers as various heuristic post-processing steps to correct the assembly graph or to link contigs into scaffolds. Such methods have allowed the identification of longer contigs than would be possible with single reads; however, they can still fail to resolve complex repeats. Thus, improved methods for incorporating mate pairs will have a strong effect on contig length in the future. Here, we introduce the paired de Bruijn graph, a generalization of the de Bruijn graph that incorporates mate pair information into the graph structure itself instead of analyzing mate pairs at a post-processing step. This graph has the potential to be used in place of the de Bruijn graph in any de Bruijn graph based assembler, maintaining all other assembly steps such as error-correction and repeat resolution. Through assembly results on simulated error-free data, we argue that this can effectively improve the contig sizes in assembly.

Original languageEnglish (US)
Title of host publicationResearch in Computational Molecular Biology - 15th Annual International Conference, RECOMB 2011, Proceedings
Pages238-251
Number of pages14
DOIs
StatePublished - 2011
Event15th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2011 - Vancouver, BC, Canada
Duration: Mar 28 2011Mar 31 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6577 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other15th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2011
CountryCanada
CityVancouver, BC
Period3/28/113/31/11

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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