Literature DB >> 25629448

On the representation of de Bruijn graphs.

Rayan Chikhi1, Antoine Limasset, Shaun Jackman, Jared T Simpson, Paul Medvedev.   

Abstract

The de Bruijn graph plays an important role in bioinformatics, especially in the context of de novo assembly. However, the representation of the de Bruijn graph in memory is a computational bottleneck for many assemblers. Recent papers proposed a navigational data structure approach in order to improve memory usage. We prove several theoretical space lower bounds to show the limitations of these types of approaches. We further design and implement a general data structure (dbgfm) and demonstrate its use on a human whole-genome dataset, achieving space usage of 1.5 GB and a 46% improvement over previous approaches. As part of dbgfm, we develop the notion of frequency-based minimizers and show how it can be used to enumerate all maximal simple paths of the de Bruijn graph using only 43 MB of memory. Finally, we demonstrate that our approach can be integrated into an existing assembler by modifying the ABySS software to use dbgfm.

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Mesh:

Year:  2015        PMID: 25629448     DOI: 10.1089/cmb.2014.0160

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  9 in total

1.  The design and construction of reference pangenome graphs with minigraph.

Authors:  Heng Li; Xiaowen Feng; Chong Chu
Journal:  Genome Biol       Date:  2020-10-16       Impact factor: 13.583

2.  Weighted minimizer sampling improves long read mapping.

Authors:  Chirag Jain; Arang Rhie; Haowen Zhang; Claudia Chu; Brian P Walenz; Sergey Koren; Adam M Phillippy
Journal:  Bioinformatics       Date:  2020-07-01       Impact factor: 6.937

3.  Scalable, ultra-fast, and low-memory construction of compacted de Bruijn graphs with Cuttlefish 2.

Authors:  Jamshed Khan; Marek Kokot; Sebastian Deorowicz; Rob Patro
Journal:  Genome Biol       Date:  2022-09-08       Impact factor: 17.906

4.  Wheeler graphs: A framework for BWT-based data structures.

Authors:  Travis Gagie; Giovanni Manzini; Jouni Sirén
Journal:  Theor Comput Sci       Date:  2017-10-25       Impact factor: 1.002

5.  Improving the performance of minimizers and winnowing schemes.

Authors:  Guillaume Marçais; David Pellow; Daniel Bork; Yaron Orenstein; Ron Shamir; Carl Kingsford
Journal:  Bioinformatics       Date:  2017-07-15       Impact factor: 6.937

6.  Simplitigs as an efficient and scalable representation of de Bruijn graphs.

Authors:  Michael Baym; Gregory Kucherov; Karel Břinda
Journal:  Genome Biol       Date:  2021-04-06       Impact factor: 13.583

7.  A tri-tuple coordinate system derived for fast and accurate analysis of the colored de Bruijn graph-based pangenomes.

Authors:  Jindan Guo; Erli Pang; Hongtao Song; Kui Lin
Journal:  BMC Bioinformatics       Date:  2021-05-27       Impact factor: 3.169

8.  Designing small universal k-mer hitting sets for improved analysis of high-throughput sequencing.

Authors:  Yaron Orenstein; David Pellow; Guillaume Marçais; Ron Shamir; Carl Kingsford
Journal:  PLoS Comput Biol       Date:  2017-10-02       Impact factor: 4.475

9.  Integrating long-range connectivity information into de Bruijn graphs.

Authors:  Isaac Turner; Kiran V Garimella; Zamin Iqbal; Gil McVean
Journal:  Bioinformatics       Date:  2018-08-01       Impact factor: 6.937

  9 in total

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