Setting objective thresholds for rare event detection in flow cytometry.

Richards, Adam J

Staats, Janet

Enzor, Jennifer

McKinnon, Katherine

Frelinger, Jacob

Denny, Thomas N

Weinhold, Kent J

Chan, Cliburn

Netherlands

2017-06-01T19:24:13Z

2017-06-01T19:24:13Z

2014-07

The accurate identification of rare antigen-specific cytokine positive cells from peripheral blood mononuclear cells (PBMC) after antigenic stimulation in an intracellular staining (ICS) flow cytometry assay is challenging, as cytokine positive events may be fairly diffusely distributed and lack an obvious separation from the negative population. Traditionally, the approach by flow operators has been to manually set a positivity threshold to partition events into cytokine-positive and cytokine-negative. This approach suffers from subjectivity and inconsistency across different flow operators. The use of statistical clustering methods does not remove the need to find an objective threshold between between positive and negative events since consistent identification of rare event subsets is highly challenging for automated algorithms, especially when there is distributional overlap between the positive and negative events ("smear"). We present a new approach, based on the Fβ measure, that is similar to manual thresholding in providing a hard cutoff, but has the advantage of being determined objectively. The performance of this algorithm is compared with results obtained by expert visual gating. Several ICS data sets from the External Quality Assurance Program Oversight Laboratory (EQAPOL) proficiency program were used to make the comparisons. We first show that visually determined thresholds are difficult to reproduce and pose a problem when comparing results across operators or laboratories, as well as problems that occur with the use of commonly employed clustering algorithms. In contrast, a single parameterization for the Fβ method performs consistently across different centers, samples, and instruments because it optimizes the precision/recall tradeoff by using both negative and positive controls.

https://www.ncbi.nlm.nih.gov/pubmed/24727143

S0022-1759(14)00118-5

1872-7905

https://hdl.handle.net/10161/14686

eng

Elsevier BV

J Immunol Methods

10.1016/j.jim.2014.04.002

Automated analysis

ICS

Positivity

Rare events

Reproducibility

Standardization

Algorithms

Automation, Laboratory

Biomarkers

Cytokines

Flow Cytometry

Guideline Adherence

Humans

Laboratories

Laboratory Proficiency Testing

Leukocytes, Mononuclear

Monitoring, Immunologic

Observer Variation

Practice Guidelines as Topic

Predictive Value of Tests

Program Development

Quality Control

Quality Indicators, Health Care

Reproducibility of Results

Specimen Handling

Setting objective thresholds for rare event detection in flow cytometry.

Journal article

Chan, Cliburn|0000-0001-5901-6806

https://www.ncbi.nlm.nih.gov/pubmed/24727143

54

61

Basic Science Departments

Biostatistics & Bioinformatics

Clinical Science Departments

Duke

Duke Cancer Institute

Duke Human Vaccine Institute

Immunology

Institutes and Centers

Medicine

Medicine, Duke Human Vaccine Institute

Pathology

School of Medicine

Statistical Science

Surgery

Surgery, Surgical Sciences

Trinity College of Arts & Sciences

Published

409