2021•BioinformaticsOpen access

MBG: Minimizer-based sparse de Bruijn Graph construction

Mikko Rautiainen, Tobias Marschall

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Abstract

MOTIVATION: De Bruijn graphs can be constructed from short reads efficiently and have been used for many purposes. Traditionally, long-read sequencing technologies have had too high error rates for de Bruijn graph-based methods. Recently, HiFi reads have provided a combination of long-read length and low error rate, which enables de Bruijn graphs to be used with HiFi reads. RESULTS: We have implemented MBG, a tool for building sparse de Bruijn graphs from HiFi reads. MBG outperforms existing tools for building dense de Bruijn graphs and can build a graph of 50× coverage whole human genome HiFi reads in four hours on a single core. MBG also assembles the bacterial E.coli genome into a single contig in 8 s. AVAILABILITY AND IMPLEMENTATION: Package manager: https://anaconda.org/bioconda/mbg and source code: https://github.com/maickrau/MBG. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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MOTIVATION: De Bruijn graphs can be constructed from short reads efficiently and have been used for many purposes. Traditionally, long-read sequencing technologies have had too high error rates for de Bruijn graph-based methods. Recently, HiFi reads have provided a combination of long-read length and low error rate, which enables de Bruijn graphs to be used with HiFi reads. RESULTS: We have implemented MBG, a tool for building sparse de Bruijn graphs from HiFi reads. MBG outperforms existing tools for building dense de Bruijn graphs and can build a graph of 50× coverage whole human genome HiFi reads in four hours on a single core. MBG also assembles the bacterial E.coli genome into a single contig in 8 s. AVAILABILITY AND IMPLEMENTATION: Package manager: https://anaconda.org/bioconda/mbg and source code: https://github.com/maickrau/MBG. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Available abstract

MOTIVATION: De Bruijn graphs can be constructed from short reads efficiently and have been used for many purposes. Traditionally, long-read sequencing technologies have had too high error rates for de Bruijn graph-based methods. Recently, HiFi reads have provided a combination of long-read length and low error rate, which enables de Bruijn graphs to be used with HiFi reads. RESULTS: We have implemented MBG, a tool for building sparse de Bruijn graphs from HiFi reads. MBG outperforms existing tools for building dense de Bruijn graphs and can build a graph of 50× coverage whole human genome HiFi reads in four hours on a single core. MBG also assembles the bacterial E.coli genome into a single contig in 8 s. AVAILABILITY AND IMPLEMENTATION: Package manager: https://anaconda.org/bioconda/mbg and source code: https://github.com/maickrau/MBG. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Key concepts: De Bruijn sequence, De Bruijn graph, Computer science, Contig, Source code, Graph, Genome, Theoretical computer science

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