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An Invariants-based Method for Efficient Identification of Hybrid Species From Large-scale Genomic Data

Laura S. Kubatko, Julia Chifman
doi: https://doi.org/10.1101/034348
Laura S. Kubatko
1Department of Statistics
2Department of Evolution, Ecology, and Organismal Biology
3Mathematical Biosciences Institute, The Ohio State University, Columbus, OH 43210, USA
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Julia Chifman
1Department of Statistics
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Article Information

doi 
https://doi.org/10.1101/034348
History 
  • December 14, 2015.
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. Laura S. Kubatko1,2,3 and
  2. Julia Chifman1
  1. 1Department of Statistics
  2. 2Department of Evolution, Ecology, and Organismal Biology
  3. 3Mathematical Biosciences Institute, The Ohio State University, Columbus, OH 43210, USA
  1. Corresponding author:
    Laura S. Kubatko, Department of Statistics,Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH 43210, USA; E-mail: lkubatko{at}stat.osu.edu.
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Posted December 14, 2015.
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An Invariants-based Method for Efficient Identification of Hybrid Species From Large-scale Genomic Data
Laura S. Kubatko, Julia Chifman
bioRxiv 034348; doi: https://doi.org/10.1101/034348
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An Invariants-based Method for Efficient Identification of Hybrid Species From Large-scale Genomic Data
Laura S. Kubatko, Julia Chifman
bioRxiv 034348; doi: https://doi.org/10.1101/034348

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