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Sci Rep. 2016 Feb 10;6:20686. doi: 10.1038/srep20686.

Standardizing Flow Cytometry Immunophenotyping Analysis from the Human ImmunoPhenotyping Consortium.

Author information

1
Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, 98109, WA.
2
Hematology Branch, National Institutes of Health, Bethesda, Maryland, USA.
3
BD Biosciences, San Jose, CA, USA.
4
Terry Fox Laboratory , British Columbia Cancer Agency, V3J 4W6, Canada.
5
UCLA Pathology and Laboratory Medicine, Los Angeles, CA.
6
Dept of Neurology, Yale School of Medicine, New Haven, CT.
7
Baylor Institute for Immunology Research, Dallas, TX.
8
University of Cambridge, JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Cambridge Institute for Medical Research, Cambridge, UK.
9
Dept Microbiology &Immunology, University of Miami Miller School of Medicine, Miami, FL.
10
Guys and St Thomas Hospital, Guy's Hospital, London, UK.
11
School of Pharmacy and Biomolecular Sciences, University of Brighton, Brighton, BN2 4GJ, United Kingdom.
12
Brighton and Sussex Medical School, Division of Medicine, Brighton, BN1 9PS, United Kingdom.
13
Department of Informatics, J. Craig Venter Institute, La Jolla, 92037, CA.
14
School of Mathematics and Physics, University of Queensland, Brisbane, Australia.
15
The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
16
Baxter Laboratory in Stem Cell Biology, Stanford University, Stanford, California, 94305, USA.
17
University of Rochester Medical Center, School of Medicine and Dentistry, Rochester, 14642, NY.
18
Laboratory of Immunology, National Eye Institute, National Institutes of Health, Bethesda, Maryland, USA.
19
Department of Medical Genetics, University of British Columbia, Canada.
20
Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, 94305, CA.
21
NHLBI Flow Cytometry Core, NIH, Bethesda, 20892, MD.

Abstract

Standardization of immunophenotyping requires careful attention to reagents, sample handling, instrument setup, and data analysis, and is essential for successful cross-study and cross-center comparison of data. Experts developed five standardized, eight-color panels for identification of major immune cell subsets in peripheral blood. These were produced as pre-configured, lyophilized, reagents in 96-well plates. We present the results of a coordinated analysis of samples across nine laboratories using these panels with standardized operating procedures (SOPs). Manual gating was performed by each site and by a central site. Automated gating algorithms were developed and tested by the FlowCAP consortium. Centralized manual gating can reduce cross-center variability, and we sought to determine whether automated methods could streamline and standardize the analysis. Within-site variability was low in all experiments, but cross-site variability was lower when central analysis was performed in comparison with site-specific analysis. It was also lower for clearly defined cell subsets than those based on dim markers and for rare populations. Automated gating was able to match the performance of central manual analysis for all tested panels, exhibiting little to no bias and comparable variability. Standardized staining, data collection, and automated gating can increase power, reduce variability, and streamline analysis for immunophenotyping.

PMID:
26861911
PMCID:
PMC4748244
DOI:
10.1038/srep20686
[Indexed for MEDLINE]
Free PMC Article
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