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happi: a Hierarchical Approach to Pangenomics Inference

Pauline Trinh, David S. Clausen, View ORCID ProfileAmy D. Willis
doi: https://doi.org/10.1101/2022.04.26.489591
Pauline Trinh
1Department of Environmental & Occupational Health Sciences, University of Washington
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David S. Clausen
2Department of Biostatistics, University of Washington
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Amy D. Willis
2Department of Biostatistics, University of Washington
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Article Information

doi 
https://doi.org/10.1101/2022.04.26.489591
History 
  • April 28, 2022.
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 4.0 International license.

Author Information

  1. Pauline Trinh1,
  2. David S. Clausen2 and
  3. Amy D. Willis2
  1. 1Department of Environmental & Occupational Health Sciences, University of Washington
  2. 2Department of Biostatistics, University of Washington
  1. * Corresponding author; email: adwillis{at}uw.edu
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Posted April 28, 2022.
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happi: a Hierarchical Approach to Pangenomics Inference
Pauline Trinh, David S. Clausen, Amy D. Willis
bioRxiv 2022.04.26.489591; doi: https://doi.org/10.1101/2022.04.26.489591
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happi: a Hierarchical Approach to Pangenomics Inference
Pauline Trinh, David S. Clausen, Amy D. Willis
bioRxiv 2022.04.26.489591; doi: https://doi.org/10.1101/2022.04.26.489591

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