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A resource-efficient tool for mixed model association analysis of large-scale data

Longda Jiang, Zhili Zheng, Ting Qi, Kathryn E. Kemper, View ORCID ProfileNaomi R. Wray, Peter M. Visscher, View ORCID ProfileJian Yang
doi: https://doi.org/10.1101/598110
Longda Jiang
1Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
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Zhili Zheng
1Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
2Institute for Advanced Research, Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
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Ting Qi
1Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
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Kathryn E. Kemper
1Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
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Naomi R. Wray
1Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
3Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia
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  • ORCID record for Naomi R. Wray
Peter M. Visscher
1Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
3Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia
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Jian Yang
1Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
2Institute for Advanced Research, Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
3Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia
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  • ORCID record for Jian Yang
  • For correspondence: jian.yang@uq.edu.au
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Article Information

doi 
https://doi.org/10.1101/598110
History 
  • April 11, 2019.

Article Versions

  • You are currently viewing Version 1 of this article (April 11, 2019 - 14:19).
  • View Version 2, the most recent version of this article.
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. Longda Jiang1,$,
  2. Zhili Zheng1,2,$,
  3. Ting Qi1,
  4. Kathryn E. Kemper1,
  5. Naomi R. Wray1,3,
  6. Peter M. Visscher1,3 and
  7. Jian Yang1,2,3,*
  1. 1Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
  2. 2Institute for Advanced Research, Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
  3. 3Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia
  1. ↵*Correspondence: Jian Yang (jian.yang{at}uq.edu.au)
  1. ↵$ These authors contributed equally to this work.

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Posted April 11, 2019.
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A resource-efficient tool for mixed model association analysis of large-scale data
Longda Jiang, Zhili Zheng, Ting Qi, Kathryn E. Kemper, Naomi R. Wray, Peter M. Visscher, Jian Yang
bioRxiv 598110; doi: https://doi.org/10.1101/598110
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A resource-efficient tool for mixed model association analysis of large-scale data
Longda Jiang, Zhili Zheng, Ting Qi, Kathryn E. Kemper, Naomi R. Wray, Peter M. Visscher, Jian Yang
bioRxiv 598110; doi: https://doi.org/10.1101/598110

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