flowCL: ontology-based cell population labelling in flow cytometry

Mélanie Courtot; Justin Meskas; Alexander D Diehl; Radina Droumeva; Raphael Gottardo; Adrin Jalali; Mohammad Jafar Taghiyar; Holden T Maecker; J Philip McCoy; Alan Ruttenberg; Richard H Scheuermann; Ryan R Brinkman

doi:10.1093/bioinformatics/btu807

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.

Affiliations

¹ Molecular Biology and Biochemistry Department, Simon Fraser University, Burnaby, BC V5A 1S6, Canada, Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada, Department of Neurology, University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, NY 14203, USA, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA, Center for Human Immunology, Autoimmunity and Inflammation, National Institutes of Health, Bethesda, MD 20892, USA, School of Dental Medicine, University at Buffalo, NY 14214-8006, USA, J. Craig Venter Institute, La Jolla, CA 92037, USA, Department of Pathology, University of California, San Diego, CA 92093, USA.
² Molecular Biology and Biochemistry Department, Simon Fraser University, Burnaby, BC V5A 1S6, Canada, Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada, Department of Neurology, University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, NY 14203, USA, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA, Center for Human Immunology, Autoimmunity and Inflammation, National Institutes of Health, Bethesda, MD 20892, USA, School of Dental Medicine, University at Buffalo, NY 14214-8006, USA, J. Craig Venter Institute, La Jolla, CA 92037, USA, Department of Pathology, University of California, San Diego, CA 92093, USA. Molecular Biology and Biochemistry Department, Simon Fraser University, Burnaby, BC V5A 1S6, Canada, Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada, Department of Neurology, University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, NY 14203, USA, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA, Center for Human Immunology, Autoimmunity and Inflammation, National Institutes of Health, Bethesda, MD 20892, USA, School of Dental Medicine, University at Buffalo, NY 14214-8006, USA, J. Craig Venter Institute, La Jolla, CA 92037, USA, Department of Pathology, University of California, San Diego, CA 92093, USA.

Abstract

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*

Substances

CCR7 protein, human
Receptors, CCR7
Leukocyte Common Antigens

flowCL: ontology-based cell population labelling in flow cytometry

Authors

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Abstract

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MeSH terms

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