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IMIX: A multivariate mixture model approach to integrative analysis of multiple types of omics data

View ORCID ProfileZiqiao Wang, View ORCID ProfilePeng Wei
doi: https://doi.org/10.1101/2020.06.23.167312
Ziqiao Wang
1Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
2The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, Texas, USA
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Peng Wei
1Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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  • For correspondence: pwei2@mdanderson.org
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Article Information

doi 
https://doi.org/10.1101/2020.06.23.167312
History 
  • June 24, 2020.
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. Ziqiao Wang1,2 and
  2. Peng Wei1,*
  1. 1Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
  2. 2The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, Texas, USA
  1. ↵*Correspondence should be addressed to: Peng Wei, PhD, 1400 Pressler St, Unit 1411, Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Email: pwei2{at}mdanderson.org
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Posted June 24, 2020.
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IMIX: A multivariate mixture model approach to integrative analysis of multiple types of omics data
Ziqiao Wang, Peng Wei
bioRxiv 2020.06.23.167312; doi: https://doi.org/10.1101/2020.06.23.167312
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IMIX: A multivariate mixture model approach to integrative analysis of multiple types of omics data
Ziqiao Wang, Peng Wei
bioRxiv 2020.06.23.167312; doi: https://doi.org/10.1101/2020.06.23.167312

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