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Development of an automated analysis system for data from flow cytometric intracellular cytokine staining assays from clinical vaccine trials
Author(s) -
Shulman Nicholas,
Bellew Matthew,
Snelling George,
Carter Donald,
Huang Yunda,
Li Hongli,
Self Steven G.,
McElrath M. Juliana,
De Rosa Stephen C.
Publication year - 2008
Publication title -
cytometry part a
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.316
H-Index - 90
eISSN - 1552-4930
pISSN - 1552-4922
DOI - 10.1002/cyto.a.20600
Subject(s) - computer science , software , data mining , bioconductor , clinical trial , flow cytometry , medicine , immunology , pathology , biology , biochemistry , gene , programming language
Abstract Intracellular cytokine staining (ICS) by multiparameter flow cytometry is one of the primary methods for determining T‐cell immunogenicity in HIV‐1 clinical vaccine trials. Data analysis requires considerable expertise and time. The amount of data is quickly increasing as more and larger trials are performed, and thus there is a critical need for high‐throughput methods of data analysis. A web‐based flow cytometric analysis system, LabKey Flow, was developed for the analyses of data from standardized ICS assays. Using a gating template created manually in commercially available flow cytometric analysis software, the system automatically compensates and analyzes all data sets. Quality control queries were designed to identify potentially incorrect sample collections. Comparison of the semiautomated analysis performed by LabKey Flow and the manual analysis performed using FlowJo software demonstrated excellent concordance (concordance correlation coefficient > 0.990). Manual inspection of the analyses performed by LabKey Flow for eight‐color ICS data files from several clinical vaccine trials indicated that template gates can appropriately be used for most data sets. Thus, the semiautomated LabKey Flow analysis system can accurately analyze large ICS data files. Routine use of the system does not require specialized expertise. This high‐throughput analysis will provide great utility for rapid evaluation of complex multiparameter flow cytometric measurements collected from large clinical trials. © 2008 International Society for Advancement of Cytometry