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Multiscale PHATE Exploration of SARS-CoV-2 Data Reveals Multimodal Signatures of Disease

Manik Kuchroo, Jessie Huang, Patrick Wong, Jean-Christophe Grenier, Dennis Shung, Alexander Tong, Carolina Lucas, Jon Klein, Daniel Burkhardt, Scott Gigante, Abhinav Godavarthi, Benjamin Israelow, Tianyang Mao, Ji Eun Oh, Julio Silva, Takehiro Takahashi, Camila D. Odio, Arnau Casanovas-Massana, John Fournier, Yale IMPACT Team, Shelli Farhadian, Charles S. Dela Cruz, Albert I. Ko, F. Perry Wilson, Julie Hussin, Guy Wolf, View ORCID ProfileAkiko Iwasaki, Smita Krishnaswamy
doi: https://doi.org/10.1101/2020.11.15.383661
Manik Kuchroo
1Department of Neuroscience, Yale University, New Haven, CT
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Jessie Huang
2Department of Computer Science, Yale University, New Haven, CT
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Patrick Wong
3Department of Immunobiology, Yale University, New Haven, CT
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Jean-Christophe Grenier
4Montreal Heart Institute, Montréal, Québec, Canada
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Dennis Shung
5Department of Medicine, Yale University, New Haven, CT
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Alexander Tong
2Department of Computer Science, Yale University, New Haven, CT
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Carolina Lucas
3Department of Immunobiology, Yale University, New Haven, CT
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Jon Klein
3Department of Immunobiology, Yale University, New Haven, CT
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Daniel Burkhardt
6Department of Genetics, Yale University, New Haven, CT
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Scott Gigante
7Computational Biology, Bioinformatics Program, Yale University, New Haven, CT
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Abhinav Godavarthi
8Department of Applied Mathematics, Yale University, New Haven, CT
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Benjamin Israelow
3Department of Immunobiology, Yale University, New Haven, CT
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Tianyang Mao
3Department of Immunobiology, Yale University, New Haven, CT
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Ji Eun Oh
3Department of Immunobiology, Yale University, New Haven, CT
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Julio Silva
3Department of Immunobiology, Yale University, New Haven, CT
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Takehiro Takahashi
3Department of Immunobiology, Yale University, New Haven, CT
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Camila D. Odio
5Department of Medicine, Yale University, New Haven, CT
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Arnau Casanovas-Massana
9Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT
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John Fournier
10Department of Medicine, Section of Infectious Diseases, Yale University School of Medicine, New Haven, CT
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11A list of authors and their affiliations appears at the end of the paper
Shelli Farhadian
10Department of Medicine, Section of Infectious Diseases, Yale University School of Medicine, New Haven, CT
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Charles S. Dela Cruz
12Department of Medicine, Section of Pulmonary and Critical Care Medicine, Yale University School of Medicine, New Haven, CT
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Albert I. Ko
9Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT
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F. Perry Wilson
13Clinical and Translational Research Accelerator, Department of Medicine, Yale University, New Haven CT
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Julie Hussin
4Montreal Heart Institute, Montréal, Québec, Canada
14Faculty of Medicine, Université de Montréal, Québec, Canada
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Guy Wolf
15Mila – Quebec AI institute, Montréal, Quebec, Canada
16Department of Mathematics and Statistics, Université de Montréal, Montréal, Quebec, Canada
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Akiko Iwasaki
3Department of Immunobiology, Yale University, New Haven, CT
17Howard Hughes Medical Institute, Chevy Chase, MD, USA
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  • ORCID record for Akiko Iwasaki
  • For correspondence: smita.krishnaswamy@yale.edu akiko.iwasaki@yale.edu
Smita Krishnaswamy
2Department of Computer Science, Yale University, New Haven, CT
6Department of Genetics, Yale University, New Haven, CT
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  • For correspondence: smita.krishnaswamy@yale.edu akiko.iwasaki@yale.edu
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1 Summary

The biomedical community is producing increasingly high dimensional datasets, integrated from hundreds of patient samples, which current computational techniques struggle to explore. To uncover biological meaning from these complex datasets, we present an approach called Multiscale PHATE, which learns abstracted biological features from data that can be directly predictive of disease. Built on a continuous coarse graining process called diffusion condensation, Multiscale PHATE creates a tree of data granularities that can be cut at coarse levels for high level summarizations of data, as well as at fine levels for detailed representations on subsets. We apply Multiscale PHATE to study the immune response to COVID-19 in 54 million cells from 168 hospitalized patients. Through our analysis of patient samples, we identify CD16hi CD66blo neutrophil and IFNγ+GranzymeB+ Th17 cell responses enriched in patients who die. Further, we show that population groupings Multiscale PHATE discovers can be directly fed into a classifier to predict disease outcome. We also use Multiscale PHATE-derived features to construct two different manifolds of patients, one from abstracted flow cytometry features and another directly on patient clinical features, both associating immune subsets and clinical markers with outcome.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • ↵§ Jointly supervised work.

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.
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Posted November 17, 2020.
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Multiscale PHATE Exploration of SARS-CoV-2 Data Reveals Multimodal Signatures of Disease
Manik Kuchroo, Jessie Huang, Patrick Wong, Jean-Christophe Grenier, Dennis Shung, Alexander Tong, Carolina Lucas, Jon Klein, Daniel Burkhardt, Scott Gigante, Abhinav Godavarthi, Benjamin Israelow, Tianyang Mao, Ji Eun Oh, Julio Silva, Takehiro Takahashi, Camila D. Odio, Arnau Casanovas-Massana, John Fournier, Yale IMPACT Team, Shelli Farhadian, Charles S. Dela Cruz, Albert I. Ko, F. Perry Wilson, Julie Hussin, Guy Wolf, Akiko Iwasaki, Smita Krishnaswamy
bioRxiv 2020.11.15.383661; doi: https://doi.org/10.1101/2020.11.15.383661
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Multiscale PHATE Exploration of SARS-CoV-2 Data Reveals Multimodal Signatures of Disease
Manik Kuchroo, Jessie Huang, Patrick Wong, Jean-Christophe Grenier, Dennis Shung, Alexander Tong, Carolina Lucas, Jon Klein, Daniel Burkhardt, Scott Gigante, Abhinav Godavarthi, Benjamin Israelow, Tianyang Mao, Ji Eun Oh, Julio Silva, Takehiro Takahashi, Camila D. Odio, Arnau Casanovas-Massana, John Fournier, Yale IMPACT Team, Shelli Farhadian, Charles S. Dela Cruz, Albert I. Ko, F. Perry Wilson, Julie Hussin, Guy Wolf, Akiko Iwasaki, Smita Krishnaswamy
bioRxiv 2020.11.15.383661; doi: https://doi.org/10.1101/2020.11.15.383661

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