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Overlap graphs and de Bruijn graphs: data structures for de novo genome assembly in the big data era

Authors :
Stefano Beretta
Yuri Pirola
Paola Bonizzoni
Murray Patterson
Marco Previtali
Gianluca Della Vedova
Raffaella Rizzi
Rizzi, R
Beretta, S
Patterson, M
Pirola, Y
Previtali, M
Della Vedova, G
Bonizzoni, P
Source :
Quantitative Biology. 7:278-292
Publication Year :
2019
Publisher :
Engineering Sciences Press, 2019.

Abstract

Background: De novo genome assembly relies on two kinds of graphs: de Bruijn graphs and overlap graphs. Overlap graphs are the basis for the Celera assembler, while de Bruijn graphs have become the dominant technical device in the last decade. Those two kinds of graphs are collectively called assembly graphs. Results: In this review, we discuss the most recent advances in the problem of constructing, representing and navigating assembly graphs, focusing on very large datasets. We will also explore some computational techniques, such as the Bloom filter, to compactly store graphs while keeping all functionalities intact. Conclusions: We complete our analysis with a discussion on the algorithmic issues of assembling from long reads (e.g., PacBio and Oxford Nanopore). Finally, we present some of the most relevant open problems in this field. [Figure not available: see fulltext.]

Details

ISSN :
20954697 and 20954689
Volume :
7
Database :
OpenAIRE
Journal :
Quantitative Biology
Accession number :
edsair.doi.dedup.....548b232c8690c4019dad42d93dd535c9
Full Text :
https://doi.org/10.1007/s40484-019-0181-x