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16GT: a fast and sensitive variant caller using a 16-genotype probabilistic model

View ORCID ProfileRuibang Luo, View ORCID ProfileMichael C. Schatz, View ORCID ProfileSteven L. Salzberg
doi: https://doi.org/10.1101/111393
Ruibang Luo
1Department of Computer Science, Johns Hopkins University,
2Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine,
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Michael C. Schatz
1Department of Computer Science, Johns Hopkins University,
2Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine,
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Steven L. Salzberg
1Department of Computer Science, Johns Hopkins University,
2Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine,
3Departments of Biomedical Engineering and Biostatistics, Johns Hopkins University
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Article Information

doi 
https://doi.org/10.1101/111393
History 
  • February 24, 2017.
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-NC-ND 4.0 International license.

Author Information

  1. Ruibang Luo1,2,*,
  2. Michael C. Schatz1,2 and
  3. Steven L. Salzberg1,2,3
  1. 1Department of Computer Science, Johns Hopkins University,
  2. 2Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine,
  3. 3Departments of Biomedical Engineering and Biostatistics, Johns Hopkins University
  1. ↵*To whom correspondence should be addressed.
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Posted February 24, 2017.
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16GT: a fast and sensitive variant caller using a 16-genotype probabilistic model
Ruibang Luo, Michael C. Schatz, Steven L. Salzberg
bioRxiv 111393; doi: https://doi.org/10.1101/111393
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16GT: a fast and sensitive variant caller using a 16-genotype probabilistic model
Ruibang Luo, Michael C. Schatz, Steven L. Salzberg
bioRxiv 111393; doi: https://doi.org/10.1101/111393

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