4.7 Article

flowDensity: reproducing manual gating of flow cytometry data by automated density-based cell population identification

Journal

BIOINFORMATICS
Volume 31, Issue 4, Pages 606-607

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btu677

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Funding

  1. National Institutes of Health [R01 EB008400]
  2. Human Immunology Consortium [U19 AI089986]
  3. National Science and Engineering Research Council

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flowDensity facilitates reproducible, high-throughput analysis of flow cytometry data by automating a predefined manual gating approach. The algorithm is based on a sequential bivariate gating approach that generates a set of predefined cell populations. It chooses the best cut-off for individual markers using characteristics of the density distribution. The Supplementary Material is linked to the online version of the manuscript.

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