Mass Cytometry pp 309-332 | Cite as

Supervised Machine Learning with CITRUS for Single Cell Biomarker Discovery

  • Hannah G. Polikowsky
  • Katherine A. Drake
Part of the Methods in Molecular Biology book series (MIMB, volume 1989)


CITRUS is a supervised machine learning algorithm designed to analyze single cell data, identify cell populations, and identify changes in the frequencies or functional marker expression patterns of those populations that are significantly associated with an outcome. The algorithm is a black box that includes steps to cluster cell populations, characterize these populations, and identify the significant characteristics. This chapter describes how to optimize the use of CITRUS by combining it with upstream and downstream data analysis and visualization tools.

Key words

CITRUS Biomarker discovery Supervised machine learning viSNE 


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Hannah G. Polikowsky
    • 1
  • Katherine A. Drake
    • 1
  1. 1.Cytobank, IncSanta ClaraUSA

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