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Allows variable read lengths while tolerating a significant level of sequencing error. MaSuRCa combines the efficiency of the de Bruijn graph and Overlap-Layout-Consensus (OLC) approaches. It transforms large numbers of paired-end reads into a much smaller number of longer ‘superreads’. The tool can significantly improve its assemblies when the original data are augmented with long reads. It has been used to assemble de novo a variety of genomes, sometimes improving on published genomes using added data, sometimes creating the first publicly available draft genome for the species.

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MaSuRCA classification

MaSuRCA specifications

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Command line interface
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MaSuRCA distribution


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MaSuRCA support


  • Aleksey Zimin <>


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Institute for Physical Sciences and Technology, University of Maryland, College Park, MD, USA; Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Mathematics, University of Maryland, College Park, MD, USA; Department of Physics, University of Maryland, College Park, MD, USA

Funding source(s)

Supported by National Research Initiative competitive grants 2009-35205-05209 and 2008-04049 from the United States Department of Agriculture National Institute of Food and Agriculture; National Institutes of Health grants R01-HG002945 and R01-HG006677.

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