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flowCL: ontology-based cell population labelling in flow cytometry.

作者信息

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

机构信息

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. 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.

出版信息

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


DOI:10.1093/bioinformatics/btu807
PMID:25481008
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4393520/
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.

摘要

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本文引用的文献

[1]
flowDensity: reproducing manual gating of flow cytometry data by automated density-based cell population identification.

Bioinformatics. 2015-2-15

[2]
OpenCyto: an open source infrastructure for scalable, robust, reproducible, and automated, end-to-end flow cytometry data analysis.

PLoS Comput Biol. 2014-8-28

[3]
Enhanced flowType/RchyOptimyx: a BioConductor pipeline for discovery in high-dimensional cytometry data.

Bioinformatics. 2014-1-8

[4]
Standardizing immunophenotyping for the Human Immunology Project.

Nat Rev Immunol. 2012-2-17

[5]
Elucidation of seventeen human peripheral blood B-cell subsets and quantification of the tetanus response using a density-based method for the automated identification of cell populations in multidimensional flow cytometry data.

Cytometry B Clin Cytom. 2010

[6]
Hematopoietic cell types: prototype for a revised cell ontology.

J Biomed Inform. 2010-2-1

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