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

Bioinformatics. 2015 Feb 15;31(4):606-7. doi: 10.1093/bioinformatics/btu677. Epub 2014 Oct 16.

Abstract

Summary: 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.

Availability and implementation: R source code freely available through BioConductor (http://master.bioconductor.org/packages/devel/bioc/html/flowDensity.html.). Data available from FlowRepository.org (dataset FR-FCM-ZZBW).

Contact: rbrinkman@bccrc.ca

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Biomarkers
  • Cell Physiological Phenomena*
  • Cluster Analysis
  • Computational Biology / methods*
  • Databases, Factual
  • Flow Cytometry / methods*
  • Humans
  • Software*

Substances

  • Biomarkers