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Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences

View ORCID ProfileAnqi Zhu, Joseph G. Ibrahim, View ORCID ProfileMichael I. Love
doi: https://doi.org/10.1101/303255
Anqi Zhu
1department of Biostatistics, University of North Carolina-Chapel Hill
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Joseph G. Ibrahim
1department of Biostatistics, University of North Carolina-Chapel Hill
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Michael I. Love
1department of Biostatistics, University of North Carolina-Chapel Hill
2Department of Genetics, University of North Carolina-Chapel Hill
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  • For correspondence: michaelisaiahlove@gmail.com
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Article Information

doi 
https://doi.org/10.1101/303255
History 
  • April 17, 2018.
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. Anqi Zhu1,
  2. Joseph G. Ibrahim1 and
  3. Michael I. Love*,1,2
  1. 1department of Biostatistics, University of North Carolina-Chapel Hill
  2. 2Department of Genetics, University of North Carolina-Chapel Hill
  1. ↵*michaelisaiahlove{at}gmail.com
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Posted April 17, 2018.
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Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences
Anqi Zhu, Joseph G. Ibrahim, Michael I. Love
bioRxiv 303255; doi: https://doi.org/10.1101/303255
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Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences
Anqi Zhu, Joseph G. Ibrahim, Michael I. Love
bioRxiv 303255; doi: https://doi.org/10.1101/303255

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