ArticleProceedings of the National Academy of Sciences of the United States of America2013
Application of user-guided automated cytometric data analysis to large-scale immunoprofiling of invariant natural killer T cells.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- MarsGT: Multi-omics analysis for rare population inference using single-cell graph transformer.Nature communications · 2024Article
- Review
- Leveraging blood and tissue CD4+ T cell heterogeneity at the single cell level to identify mechanisms of disease in rheumatoid arthritis.Current opinion in immunology · 2017Review
- BayesFlow: latent modeling of flow cytometry cell populations.BMC bioinformatics · 2016Article
- Immune cell profiling to guide therapeutic decisions in rheumatic diseases.Nature reviews. Rheumatology · 2015Review
- flowDensity: reproducing manual gating of flow cytometry data by automated density-based cell population identification.Bioinformatics (Oxford, England) · 2015Article
- OpenCyto: an open source infrastructure for scalable, robust, reproducible, and automated, end-to-end flow cytometry data analysis.PLoS computational biology · 2014Article
- Regulation of gene expression in autoimmune disease loci and the genetic basis of proliferation in CD4+ effector memory T cells.PLoS genetics · 2014Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Defining and characterizing pathologies of the immune system requires precise and accurate quantification of abundances and functions of cellular subsets via cytometric studies. At this time, data analysis relies on manual gating, which is a major source of variability in large-scale studies. We devised an automated, user-guided method, X-Cyt, which specializes in rapidly and robustly identifying targeted populations of interest in large data sets. We first applied X-Cyt to quantify CD4(+) effector and central memory T cells in 236 samples, demonstrating high concordance with manual analysis (r = 0.91 and 0.95, respectively) and superior performance to other available methods. We then quantified the rare mucosal associated invariant T cell population in 35 samples, achieving manual concordance of 0.98. Finally we characterized the population dynamics of invariant natural killer T (iNKT) cells, a particularly rare peripheral lymphocyte, in 110 individuals by assaying 19 markers. We demonstrated that although iNKT cell numbers and marker expression are highly variable in the population, iNKT abundance correlates with sex and age, and the expression of phenotypic and functional markers correlates closely with CD4 expression.
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Registered trials
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