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Optimizing the design of spatial genomic studies

View ORCID ProfileAndrew Jones, Diana Cai, View ORCID ProfileDidong Li, View ORCID ProfileBarbara E. Engelhardt
doi: https://doi.org/10.1101/2023.01.29.526115
Andrew Jones
1Department of Computer Science, Princeton University
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Diana Cai
1Department of Computer Science, Princeton University
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Didong Li
2Department of Biostatistics, University of North Carolina at Chapel Hill
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Barbara E. Engelhardt
3Gladstone Institutes
4Department of Biomedical Data Science, Stanford University
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  • For correspondence: barbarae@stanford.edu
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Article Information

doi 
https://doi.org/10.1101/2023.01.29.526115
History 
  • January 31, 2023.
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-ND 4.0 International license.

Author Information

  1. Andrew Jones1,
  2. Diana Cai1,
  3. Didong Li2 and
  4. Barbara E. Engelhardt3,4,*
  1. 1Department of Computer Science, Princeton University
  2. 2Department of Biostatistics, University of North Carolina at Chapel Hill
  3. 3Gladstone Institutes
  4. 4Department of Biomedical Data Science, Stanford University
  1. ↵*Corresponding author; email: barbarae{at}stanford.edu
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Posted January 31, 2023.
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Optimizing the design of spatial genomic studies
Andrew Jones, Diana Cai, Didong Li, Barbara E. Engelhardt
bioRxiv 2023.01.29.526115; doi: https://doi.org/10.1101/2023.01.29.526115
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Optimizing the design of spatial genomic studies
Andrew Jones, Diana Cai, Didong Li, Barbara E. Engelhardt
bioRxiv 2023.01.29.526115; doi: https://doi.org/10.1101/2023.01.29.526115

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