flowCL: ontology-based cell population labelling in flow cytometry

Bioinformatics. 2015 Apr 15;31(8):1337-9. doi: 10.1093/bioinformatics/btu807. Epub 2014 Dec 6.


Motivation: Finding one or more cell populations of interest, such as those correlating to a specific disease, is critical when analysing flow cytometry data. However, labelling of cell populations is not well defined, making it difficult to integrate the output of algorithms to external knowledge sources.

Results: We developed flowCL, a software package that performs semantic labelling of cell populations based on their surface markers and applied it to labelling of the Federation of Clinical Immunology Societies Human Immunology Project Consortium lyoplate populations as a use case.

Conclusion: By providing automated labelling of cell populations based on their immunophenotype, flowCL allows for unambiguous and reproducible identification of standardized cell types.

Availability and implementation: Code, R script and documentation are available under the Artistic 2.0 license through Bioconductor (http://www.bioconductor.org/packages/devel/bioc/html/flowCL.html).

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*
  • Cell Physiological Phenomena*
  • Flow Cytometry / methods*
  • Gene Ontology*
  • Humans
  • Immunophenotyping / methods*
  • Leukocyte Common Antigens / analysis
  • Receptors, CCR7 / analysis
  • Software*


  • CCR7 protein, human
  • Receptors, CCR7
  • Leukocyte Common Antigens