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Citations per year

Number of citations per year for the bioinformatics software tool MaSuRCA

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This map represents all the scientific publications referring to MaSuRCA per scientific context
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MaSuRCA specifications


Unique identifier OMICS_00020
Name MaSuRCA
Alternative name Maryland Super-Read Celera Assembler
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Stability Stable
Maintained Yes


No version available


  • person_outline Steven Salzberg
  • person_outline Aleksey Zimin

Publication for Maryland Super-Read Celera Assembler


The MaSuRCA genome assembler.

2013 Bioinformatics
PMCID: 3799473
PMID: 23990416
DOI: 10.1093/bioinformatics/btt476

MaSuRCA citations


Comparison of the Chinese bamboo partridge and red Junglefowl genome sequences highlights the importance of demography in genome evolution

BMC Genomics
PMCID: 5941490
PMID: 29739321
DOI: 10.1186/s12864-018-4711-0

[…] Kmer frequencies using SOAPec v2.01 with default settings []. We then built de novo assemblies from the edited reads using SOAPdenovo2 v2.04 [] and ABySS v1.9.0 []. We also assembled the genome with MaSuRCA v2.3.2 [], which uses its own raw data quality control tools. For computational feasibility, the three assemblies used Kmer values of 63, 63, and 35 respectively, and we merged scaffolds with […]


Whole genome de novo sequencing reveals unique genes that contributed to the adaptive evolution of the Mikado pheasant

PMCID: 5941149
PMID: 29722814
DOI: 10.1093/gigascience/giy044
call_split See protocol

[…] : TruSeq3-PE.fa:2:30:15 SLIDINGWINDOW:4:20 MINLEN:100”) [] and NextClip (version 1.3.1) [] with default parameters were used to trim sequencing reads. Genome assembly into contigs was performed using MaSuRCA (version 2.3.2) [] with settings based on the instruction manual. ALLPATHS-LG (ALLPATHS-LG, RRID:SCR_010742, version 49722) [], Newbler (version 2.9) [] both with default parameters, JR (versi […]


Tracking the NGS revolution: managing life science research on shared high performance computing clusters

PMCID: 5928410
PMID: 29659792
DOI: 10.1093/gigascience/giy028

[…] mputation for statistical inference []) support task continuation on an ad hoc basis, but formal intermediate checkpoints are found in only a handful of multistage tools such as the genome assemblers MaSuRCA [] and ABySS [].Second, NGS software tools could provide the ability to limit the amount of RAM used. NGS tools that allow the user to specify memory limits are few in number; Java-based tools […]


Genome Sequences of Apibacter spp., Gut Symbionts of Asian Honey Bees

Genome Biol Evol
PMCID: 5913662
PMID: 29635372
DOI: 10.1093/gbe/evy076

[…] the University of Texas at Austin (). In total, 2.6 million 300-bp Illumina MiSeq reads were acquired for strains wkB180, wkB301, and wkB309. Reads for strains wkB180 and wkB301 were assembled using MaSuRCA 3.2.2 (). Assembly of strain wkB309 was performed with Velvet 1.2.10 () and CLC Genomics Workbench 5.5 (QIAGEN), and improved by mapping reads back onto assembled contigs using Bowtie 2 () and […]


De novo draft assembly of the Botrylloides leachii genome provides further insight into tunicate evolution

Sci Rep
PMCID: 5882950
PMID: 29615780
DOI: 10.1038/s41598-018-23749-w
call_split See protocol

[…] First, both libraries were assembled together in parallel, using a k-mer size of 63 (when available) following the results from KmerGenie, by five assemblers: ABySS, Velvet, SOAPdenovo2, ALLPATHS-LG, MaSuRCA. The MaSuRCA assembler was run twice, once running the adapter filtering function (here termed “MaSuRCA-filtered”), the other without it (termed simply “MaSuRCA”). Their respective quality was […]


A guide to sequence your favorite plant genomes

Appl Plant Sci
PMCID: 5895188
PMID: 29732260
DOI: 10.1002/aps3.1030

[…] ugh PacBio or Nanopore coverage for a large genome is not always possible, but one can reduce the cost by generating cheap short‐read data and adopting a hybrid assembly approach. This can be done in MaSuRCA (Zimin et al., ), which first extends short reads into “super‐reads,” and uses these super‐reads to turn long reads into “mega‐reads.” These processed reads can then be assembled by OLC. Sever […]

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MaSuRCA institution(s)
Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA; Institute for Physical Sciences and Technology, University of Maryland, College Park, MD, USA; Department of Plant Sciences, University of California, Davis, CA, USA; National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA; Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA; Departments of Mathematics and Physics, University of Maryland, College Park, MD, USA; Departments of Biomedical Engineering, Computer Science, and Biostatistics, Johns Hopkins University, Baltimore, MD, USA
MaSuRCA funding source(s)
Supported in part by National Science Foundation (NSF) grant IOS-1238231, by National Institutes of Health (NIH) grant R01- HG006677, and by the Intramural Research Program of the National Human Genome Research Institute, NIH.

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