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NanoSim: nanopore sequence read simulator based on statistical characterization

Chen Yang, Justin Chu, René L Warren, Inanç Birol
doi: https://doi.org/10.1101/044545
Chen Yang
1Faculty of Science, University of British Columbia, Vancouver, Canada,
2Genome Science Centre, British Columbia Cancer Agency, Vancouver, Canada,
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Justin Chu
1Faculty of Science, University of British Columbia, Vancouver, Canada,
2Genome Science Centre, British Columbia Cancer Agency, Vancouver, Canada,
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René L Warren
2Genome Science Centre, British Columbia Cancer Agency, Vancouver, Canada,
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Inanç Birol
2Genome Science Centre, British Columbia Cancer Agency, Vancouver, Canada,
3Department of Medical Genetics, University of British Columbia, Vancouver, Canada,
4School of Computing Science, Simon Fraser University, Burnaby, Canada.
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Abstract

Motivation: In 2014, Oxford Nanopore Technologies (ONT) announced a new sequencing platform called MinION. The particular features of MinION reads – longer read lengths and single-molecule sequencing in particular – show potential for genome characterization. As of yet, the pre-commercial technology is exclusively available through early-access, and only a few datasets are publically available for testing. Further, no software exists that simulates MinION platform reads with genuine ONT characteristics.

Results: In this article, we introduce NanoSim, a fast and scalable read simulator that captures the technology-specific features of ONT data, and allows for adjustments upon improvement of nanopore sequencing technology.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted March 18, 2016.
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NanoSim: nanopore sequence read simulator based on statistical characterization
Chen Yang, Justin Chu, René L Warren, Inanç Birol
bioRxiv 044545; doi: https://doi.org/10.1101/044545
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NanoSim: nanopore sequence read simulator based on statistical characterization
Chen Yang, Justin Chu, René L Warren, Inanç Birol
bioRxiv 044545; doi: https://doi.org/10.1101/044545

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