Gating mass cytometry data by deep learning.

Journal: Bioinformatics (Oxford, England)
Published Date: Nov 1, 2017

Abstract

MOTIVATION: Mass cytometry or CyTOF is an emerging technology for high-dimensional multiparameter single cell analysis that overcomes many limitations of fluorescence-based flow cytometry. New methods for analyzing CyTOF data attempt to improve automation, scalability, performance and interpretation of data generated in large studies. Assigning individual cells into discrete groups of cell types (gating) involves time-consuming sequential manual steps, untenable for larger studies.

Authors

  • Huamin Li
    Applied Mathematics Program, Yale University, New Haven, CT 06511, USA.
  • Uri Shaham
    Department of Statistics, Yale University, New Haven, CT 06511, USA.
  • Kelly P Stanton
    Department of Pathology, Yale School of Medicine, New Haven, CT 06510, USA.
  • Yi Yao
    School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu, China.
  • Ruth R Montgomery
    Department of Internal Medicine, Yale School of Medicine, New Haven, CT 06520, USA.
  • Yuval Kluger
    Department of Pathology, Yale School of Medicine, New Haven, CT 06510, USA.

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