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Non-Parametric Genetic Prediction of Complex Traits with Latent Dirichlet Process Regression Models

Ping Zeng, Xiang Zhou
doi: https://doi.org/10.1101/149609
Ping Zeng
1 Department of Epidemiology and Biostatistics, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
2 Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA.
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Xiang Zhou
2 Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA.
3 Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA.
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  • For correspondence: xzhousph@umich.edu
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Article Information

doi 
https://doi.org/10.1101/149609
History 
  • June 13, 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. Ping Zeng1,2 and
  2. Xiang Zhou2,3,*
  1. 1 Department of Epidemiology and Biostatistics, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
  2. 2 Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA.
  3. 3 Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA.
  1. ↵*Correspondence and requests for materials should be addressed to XZ (email: xzhousph{at}umich.edu)
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Posted June 13, 2017.
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Non-Parametric Genetic Prediction of Complex Traits with Latent Dirichlet Process Regression Models
Ping Zeng, Xiang Zhou
bioRxiv 149609; doi: https://doi.org/10.1101/149609
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Non-Parametric Genetic Prediction of Complex Traits with Latent Dirichlet Process Regression Models
Ping Zeng, Xiang Zhou
bioRxiv 149609; doi: https://doi.org/10.1101/149609

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