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Gating mass cytometry data by deep learning

Huamin Li, Uri Shaham, Kelly P. Stanton, Yi Yao, Ruth Montgomery, Yuval Kluger
doi: https://doi.org/10.1101/054411
Huamin Li
1Applied Mathematics Program, Yale University, 51 Prospect St., New Haven, CT 06511, USA
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Uri Shaham
2Department of Statistics, Yale University, 24 Hillhouse Ave., New Haven, CT 06511, USA
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Kelly P. Stanton
3Department of Pathology and Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA
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Yi Yao
4Department of Internal Medicine, Yale School of Medicine, 333 Cedar St., New Haven, CT 06520, USA
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Ruth Montgomery
4Department of Internal Medicine, Yale School of Medicine, 333 Cedar St., New Haven, CT 06520, USA
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Yuval Kluger
1Applied Mathematics Program, Yale University, 51 Prospect St., New Haven, CT 06511, USA
3Department of Pathology and Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA
5Interdepartmental Program in Computational Biology and Bioinformatics,Yale University, New Haven, CT, USA
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  • For correspondence: yuval.kluger@yale.edu
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Posted June 20, 2017.
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Gating mass cytometry data by deep learning
Huamin Li, Uri Shaham, Kelly P. Stanton, Yi Yao, Ruth Montgomery, Yuval Kluger
bioRxiv 054411; doi: https://doi.org/10.1101/054411
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Gating mass cytometry data by deep learning
Huamin Li, Uri Shaham, Kelly P. Stanton, Yi Yao, Ruth Montgomery, Yuval Kluger
bioRxiv 054411; doi: https://doi.org/10.1101/054411

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