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OMSim : a simulator for optical map data

Giles Miclotte (UGent) , Stéphane Plaisance (UGent) , Stephane Rombauts (UGent) , Yves Van de Peer (UGent) , P. Audenaert (UGent) and Jan Fostier (UGent)
(2017) BIOINFORMATICS. 33(17). p.2740-2742
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Abstract
Motivation: The Bionano Genomics platform allows for the optical detection of short sequence patterns in very long DNA molecules (up to 2.5 Mbp). Molecules with overlapping patterns can be assembled to generate a consensus optical map of the entire genome. In turn, these optical maps can be used to validate or improve de novo genome assembly projects or to detect large-scale structural variation in genomes. Simulated optical map data can assist in the development and benchmarking of tools that operate on those data, such as alignment and assembly software. Additionally, it can help to optimize the experimental setup for a genome of interest. Such a simulator is currently not available. Results: We have developed a simulator, OMSim, that produces synthetic optical map data that mimics real Bionano Genomics data. These simulated data have been tested for compatibility with the Bionano Genomics Irys software system and the Irys-scaffolding scripts. OMSim is capable of handling very large genomes (over 30 Gbp) with high throughput and low memory requirements.
Keywords
IBCN, GENOME

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MLA
Miclotte, Giles, et al. “OMSim : A Simulator for Optical Map Data.” BIOINFORMATICS, vol. 33, no. 17, 2017, pp. 2740–42, doi:10.1093/bioinformatics/btx293.
APA
Miclotte, G., Plaisance, S., Rombauts, S., Van de Peer, Y., Audenaert, P., & Fostier, J. (2017). OMSim : a simulator for optical map data. BIOINFORMATICS, 33(17), 2740–2742. https://doi.org/10.1093/bioinformatics/btx293
Chicago author-date
Miclotte, Giles, Stéphane Plaisance, Stephane Rombauts, Yves Van de Peer, P. Audenaert, and Jan Fostier. 2017. “OMSim : A Simulator for Optical Map Data.” BIOINFORMATICS 33 (17): 2740–42. https://doi.org/10.1093/bioinformatics/btx293.
Chicago author-date (all authors)
Miclotte, Giles, Stéphane Plaisance, Stephane Rombauts, Yves Van de Peer, P. Audenaert, and Jan Fostier. 2017. “OMSim : A Simulator for Optical Map Data.” BIOINFORMATICS 33 (17): 2740–2742. doi:10.1093/bioinformatics/btx293.
Vancouver
1.
Miclotte G, Plaisance S, Rombauts S, Van de Peer Y, Audenaert P, Fostier J. OMSim : a simulator for optical map data. BIOINFORMATICS. 2017;33(17):2740–2.
IEEE
[1]
G. Miclotte, S. Plaisance, S. Rombauts, Y. Van de Peer, P. Audenaert, and J. Fostier, “OMSim : a simulator for optical map data,” BIOINFORMATICS, vol. 33, no. 17, pp. 2740–2742, 2017.
@article{8531258,
  abstract     = {{Motivation: The Bionano Genomics platform allows for the optical detection of short sequence patterns in very long DNA molecules (up to 2.5 Mbp). Molecules with overlapping patterns can be assembled to generate a consensus optical map of the entire genome. In turn, these optical maps can be used to validate or improve de novo genome assembly projects or to detect large-scale structural variation in genomes. Simulated optical map data can assist in the development and benchmarking of tools that operate on those data, such as alignment and assembly software. Additionally, it can help to optimize the experimental setup for a genome of interest. Such a simulator is currently not available. 
Results: We have developed a simulator, OMSim, that produces synthetic optical map data that mimics real Bionano Genomics data. These simulated data have been tested for compatibility with the Bionano Genomics Irys software system and the Irys-scaffolding scripts. OMSim is capable of handling very large genomes (over 30 Gbp) with high throughput and low memory requirements.}},
  author       = {{Miclotte, Giles and Plaisance, Stéphane and Rombauts, Stephane and Van de Peer, Yves and Audenaert, P. and Fostier, Jan}},
  issn         = {{1367-4803}},
  journal      = {{BIOINFORMATICS}},
  keywords     = {{IBCN,GENOME}},
  language     = {{eng}},
  number       = {{17}},
  pages        = {{2740--2742}},
  title        = {{OMSim : a simulator for optical map data}},
  url          = {{http://doi.org/10.1093/bioinformatics/btx293}},
  volume       = {{33}},
  year         = {{2017}},
}
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