Immunologic Research

, Volume 58, Issue 2–3, pp 218–223 | Cite as

AutoGate: automating analysis of flow cytometry data

  • Stephen Meehan
  • Guenther Walther
  • Wayne Moore
  • Darya Orlova
  • Connor Meehan
  • David Parks
  • Eliver Ghosn
  • Megan Philips
  • Erin Mitsunaga
  • Jeffrey Waters
  • Aaron Kantor
  • Ross Okamura
  • Solomon Owumi
  • Yang Yang
  • Leonard A. Herzenberg
  • Leonore A. Herzenberg
IMMUNOLOGY AT STANFORD UNIVERSITY

Abstract

Nowadays, one can hardly imagine biology and medicine without flow cytometry to measure CD4 T cell counts in HIV, follow bone marrow transplant patients, characterize leukemias, etc. Similarly, without flow cytometry, there would be a bleak future for stem cell deployment, HIV drug development and full characterization of the cells and cell interactions in the immune system. But while flow instruments have improved markedly, the development of automated tools for processing and analyzing flow data has lagged sorely behind. To address this deficit, we have developed automated flow analysis software technology, provisionally named AutoComp and AutoGate. AutoComp acquires sample and reagent labels from users or flow data files, and uses this information to complete the flow data compensation task. AutoGate replaces the manual subsetting capabilities provided by current analysis packages with newly defined statistical algorithms that automatically and accurately detect, display and delineate subsets in well-labeled and well-recognized formats (histograms, contour and dot plots). Users guide analyses by successively specifying axes (flow parameters) for data subset displays and selecting statistically defined subsets to be used for the next analysis round. Ultimately, this process generates analysis “trees” that can be applied to automatically guide analyses for similar samples. The first AutoComp/AutoGate version is currently in the hands of a small group of users at Stanford, Emory and NIH. When this “early adopter” phase is complete, the authors expect to distribute the software free of charge to .edu, .org and .gov users.

Keywords

Multiparameter flow cytometry Automating fluorescence compensation Automatic cell subsets identification Guiding gating strategy 

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Stephen Meehan
    • 1
    • 2
  • Guenther Walther
    • 2
  • Wayne Moore
    • 1
  • Darya Orlova
    • 1
    • 4
  • Connor Meehan
    • 3
  • David Parks
    • 1
  • Eliver Ghosn
    • 1
  • Megan Philips
    • 1
  • Erin Mitsunaga
    • 1
  • Jeffrey Waters
    • 1
  • Aaron Kantor
    • 1
  • Ross Okamura
    • 1
  • Solomon Owumi
    • 1
  • Yang Yang
    • 1
  • Leonard A. Herzenberg
    • 1
  • Leonore A. Herzenberg
    • 1
  1. 1.Department of GeneticsStanford University School of MedicineStanfordUSA
  2. 2.Department of StatisticsStanford UniversityStanfordUSA
  3. 3.Department of MathematicsCalifornia Institute of TechnologyPasadenaUSA
  4. 4.Institute of Chemical Kinetics and CombustionNovosibirskRussia

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