Minimus: a fast, lightweight genome assembler

By Daniel D. Sommer, Arthur L. Delcher, Steven L. Salzberg, Mihai Pop. BMC Bioinformatics, 2007

411 citations recorded by the source corpus.

BackgroundGenome assemblers have grown very large and complex in response to the need for algorithms to handle the challenges of large whole-genome sequencing projects. Many of the most common uses of assemblers, however, are best served by a simpler type of assembler that requires fewer software components, uses less memory, and is far easier to install and run.ResultsWe have developed the Minimus assembler to address these issues, and tested it on a range of assembly problems. We show that Minimus performs well on several small assembly tasks, including the assembly of viral genomes, individual genes, and BAC clones. In addition, we evaluate Minimus' performance in assembling bacterial genomes in order to assess its suitability as a component of a larger assembly pipeline. We show that, unlike other software currently used for these tasks, Minimus produces significantly fewer assembly errors, at the cost of generating a more fragmented assembly.ConclusionWe find that for small genomes and other small assembly tasks, Minimus is faster and far more flexible than existing tools. Due to its small size and modular design Minimus is perfectly suited to be a component of complex assembly pipelines. Minimus is released as an open-source software project and the code is available as part of the AMOS project at Sourceforge.

Subfields: Ecology, Mechanical Engineering, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/79f7b352010584cc0ed153f94d48ddd6be858dbd

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Citations in the corpus

Hybrid error correction and de novo assembly of single-molecule sequencing reads (2012, methodology): “ALLORA, a long-read assembler based on AMOS 20–22 , is computationally limited to small genomes and requires high-accuracy PacBio sequences, such as CCS, to operate.”
A cloud-compatible bioinformatics pipeline for ultrarapid pathogen identification from next-generation sequencing of clinical samples (2014, methodology): “(Simpsonetal.2009)andoverlap-layout-consensus(OLC)(Sommer et al. 2007) methods produced longer and higher quality assemblies than the use of de Bruijn algorithms alone (Supplemental Methods; Supplemental Table S22).”
SqueezeMeta, A Highly Portable, Fully Automatic Metagenomic Analysis Pipeline (2018, methodology): “In the merged mode, each metagenome will be assembled separately and the resulting contigs will be merged and joined, using cd-hit [13] for removing redundant contigs and minimus2 [14] for the merging.”
Circlator: automated circularization of genome assemblies using long sequencing reads (2015, methodology): “Currently, there are two main approaches to resolving the circular structure, based on using BLAST [12] and Minimus2 [13] to identify the common sequence at each contig end, which we shall refer to as simply BLAST and Minimus2 for the remainder of the manuscript.”
Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data (2013, methodology): “Optionally, minimus2 or similar tools can be used to connect the contigs from step (3) to further improve the continuity of the assembly and remove spurious contigs due to assembly or sequencing errors 17,18 .”
Genome assembly reborn: recent computational challenges (2009, background): “In such cases unitigs can be obtained with standalone assemblers such as Minimus [32] or newbler (assembler provided with the 454 sequencing instrument), or by examining the internal datastructures of Celera Assembler or Arachne.”
De novo bacterial genome sequencing: millions of very short reads assembled on a desktop computer. (2008, background): “High-quality sequencing data are, of course, mandatory for such projects, and the frequency of errors arising from high-throughput sequencers appears reasonable (Sundquist et al. 2007).”