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TooManyCellsInteractive: a visualization tool for dynamic exploration of single-cell data

Conor Klamann, Christie Lau, View ORCID ProfileGregory W. Schwartz
doi: https://doi.org/10.1101/2023.06.16.544954
Conor Klamann
1Data Sciences Institute, University of Toronto, Toronto, ON M5G 1Z5, Canada
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Christie Lau
2Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 1L7, Canada
3Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada
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Gregory W. Schwartz
2Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 1L7, Canada
3Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada
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  • ORCID record for Gregory W. Schwartz
  • For correspondence: gregory.schwartz@uhnresearch.ca
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Abstract

As single-cell sequencing data sets grow in size, visualizations of large cellular populations become difficult to parse and require extensive processing to identify subpopulations of cells. Managing many of these charts is laborious for technical users and unintuitive for non-technical users. To address this issue, we developed TooManyCellsInteractive (TMCI), a browser-based JavaScript application for visualizing hierarchical cellular populations as an interactive radial tree. TMCI allows users to explore, filter, and manipulate hierarchical data structures through an intuitive interface while also enabling batch export of high-quality custom graphics. Here we describe the software architecture and illustrate how TMCI has identified unique survival pathways among drug-tolerant persister cells in a pan-cancer analysis. TMCI will help guide increasingly large data visualizations and facilitate multi-resolution data exploration in a user-friendly way.

Competing Interest Statement

The authors have declared no competing interest.

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 June 18, 2023.
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TooManyCellsInteractive: a visualization tool for dynamic exploration of single-cell data
Conor Klamann, Christie Lau, Gregory W. Schwartz
bioRxiv 2023.06.16.544954; doi: https://doi.org/10.1101/2023.06.16.544954
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TooManyCellsInteractive: a visualization tool for dynamic exploration of single-cell data
Conor Klamann, Christie Lau, Gregory W. Schwartz
bioRxiv 2023.06.16.544954; doi: https://doi.org/10.1101/2023.06.16.544954

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