1. Automated Analysis of Flow Cytometry Data to Reduce Inter-Lab Variation in the Detection of Major Histocompatibility Complex Multimer-Binding T Cells
- Author
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Pedersen, Natasja Wulff, Chandran, P Anoop, Qian, Yu, Rebhahn, Jonathan, Petersen, Nadia Viborg, Hoff, Mathilde Dalsgaard, White, Scott, Lee, Alexandra J, Stanton, Rick, Halgreen, Charlotte, Jakobsen, Kivin, Mosmann, Tim, Gouttefangeas, Cécile, Chan, Cliburn, Scheuermann, Richard H, and Hadrup, Sine Reker
- Subjects
Biomedical and Clinical Sciences ,Immunology ,Bioengineering ,major histocompatibility complex multimers ,antigen-specific T cells ,automated gating ,computational analysis ,major histocompatibility complex dextramers ,flow cytometry ,Medical Microbiology ,Biochemistry and cell biology ,Genetics - Abstract
Manual analysis of flow cytometry data and subjective gate-border decisions taken by individuals continue to be a source of variation in the assessment of antigen-specific T cells when comparing data across laboratories, and also over time in individual labs. Therefore, strategies to provide automated analysis of major histocompatibility complex (MHC) multimer-binding T cells represent an attractive solution to decrease subjectivity and technical variation. The challenge of using an automated analysis approach is that MHC multimer-binding T cell populations are often rare and therefore difficult to detect. We used a highly heterogeneous dataset from a recent MHC multimer proficiency panel to assess if MHC multimer-binding CD8+ T cells could be analyzed with computational solutions currently available, and if such analyses would reduce the technical variation across different laboratories. We used three different methods, FLOw Clustering without K (FLOCK), Scalable Weighted Iterative Flow-clustering Technique (SWIFT), and ReFlow to analyze flow cytometry data files from 28 laboratories. Each laboratory screened for antigen-responsive T cell populations with frequency ranging from 0.01 to 1.5% of lymphocytes within samples from two donors. Experience from this analysis shows that all three programs can be used for the identification of high to intermediate frequency of MHC multimer-binding T cell populations, with results very similar to that of manual gating. For the less frequent populations (
- Published
- 2017