Novel data analysis method for multicolour flow cytometry links variability of multiple markers on single cells to a clinical phenotype

Abstract Multicolour Flow Cytometry (MFC) produces multidimensional analytical data on the quantitative expression of multiple markers on single cells. This data contains invaluable biomedical information on (1) the marker expressions per cell, (2) the variation in such expression across cells, (3)...

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Autores principales:	Gerjen H. Tinnevelt, Marietta Kokla, Bart Hilvering, Selma van Staveren, Rita Folcarelli, Luzheng Xue, Andries C. Bloem, Leo Koenderman, Lutgarde M. C. Buydens, Jeroen J. Jansen
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/15b0fc1fdf734f5faa8858f42b7ef7f9
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spelling	oai:doaj.org-article:15b0fc1fdf734f5faa8858f42b7ef7f92021-12-02T16:06:16ZNovel data analysis method for multicolour flow cytometry links variability of multiple markers on single cells to a clinical phenotype10.1038/s41598-017-05714-12045-2322https://doaj.org/article/15b0fc1fdf734f5faa8858f42b7ef7f92017-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-05714-1https://doaj.org/toc/2045-2322Abstract Multicolour Flow Cytometry (MFC) produces multidimensional analytical data on the quantitative expression of multiple markers on single cells. This data contains invaluable biomedical information on (1) the marker expressions per cell, (2) the variation in such expression across cells, (3) the variability of cell marker expression across samples that (4) may vary systematically between cells collected from donors and patients. Current conventional and even advanced data analysis methods for MFC data explore only a subset of these levels. The Discriminant Analysis of MultiAspect CYtometry (DAMACY) we present here provides a comprehensive view on health and disease responses by integrating all four levels. We validate DAMACY by using three distinct datasets: in vivo response of neutrophils evoked by systemic endotoxin challenge, the clonal response of leukocytes in bone marrow of acute myeloid leukaemia (AML) patients, and the complex immune response in blood of asthmatics. DAMACY provided good accuracy 91–100% in the discrimination between health and disease, on par with literature values. Additionally, the method provides figures that give insight into the marker expression and cell variability for more in-depth interpretation, that can benefit both physicians and biomedical researchers to better diagnose and monitor diseases that are reflected by changes in blood leukocytes.Gerjen H. TinneveltMarietta KoklaBart HilveringSelma van StaverenRita FolcarelliLuzheng XueAndries C. BloemLeo KoendermanLutgarde M. C. BuydensJeroen J. JansenNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Gerjen H. Tinnevelt Marietta Kokla Bart Hilvering Selma van Staveren Rita Folcarelli Luzheng Xue Andries C. Bloem Leo Koenderman Lutgarde M. C. Buydens Jeroen J. Jansen Novel data analysis method for multicolour flow cytometry links variability of multiple markers on single cells to a clinical phenotype
description	Abstract Multicolour Flow Cytometry (MFC) produces multidimensional analytical data on the quantitative expression of multiple markers on single cells. This data contains invaluable biomedical information on (1) the marker expressions per cell, (2) the variation in such expression across cells, (3) the variability of cell marker expression across samples that (4) may vary systematically between cells collected from donors and patients. Current conventional and even advanced data analysis methods for MFC data explore only a subset of these levels. The Discriminant Analysis of MultiAspect CYtometry (DAMACY) we present here provides a comprehensive view on health and disease responses by integrating all four levels. We validate DAMACY by using three distinct datasets: in vivo response of neutrophils evoked by systemic endotoxin challenge, the clonal response of leukocytes in bone marrow of acute myeloid leukaemia (AML) patients, and the complex immune response in blood of asthmatics. DAMACY provided good accuracy 91–100% in the discrimination between health and disease, on par with literature values. Additionally, the method provides figures that give insight into the marker expression and cell variability for more in-depth interpretation, that can benefit both physicians and biomedical researchers to better diagnose and monitor diseases that are reflected by changes in blood leukocytes.
format	article
author	Gerjen H. Tinnevelt Marietta Kokla Bart Hilvering Selma van Staveren Rita Folcarelli Luzheng Xue Andries C. Bloem Leo Koenderman Lutgarde M. C. Buydens Jeroen J. Jansen
author_facet	Gerjen H. Tinnevelt Marietta Kokla Bart Hilvering Selma van Staveren Rita Folcarelli Luzheng Xue Andries C. Bloem Leo Koenderman Lutgarde M. C. Buydens Jeroen J. Jansen
author_sort	Gerjen H. Tinnevelt
title	Novel data analysis method for multicolour flow cytometry links variability of multiple markers on single cells to a clinical phenotype
title_short	Novel data analysis method for multicolour flow cytometry links variability of multiple markers on single cells to a clinical phenotype
title_full	Novel data analysis method for multicolour flow cytometry links variability of multiple markers on single cells to a clinical phenotype
title_fullStr	Novel data analysis method for multicolour flow cytometry links variability of multiple markers on single cells to a clinical phenotype
title_full_unstemmed	Novel data analysis method for multicolour flow cytometry links variability of multiple markers on single cells to a clinical phenotype
title_sort	novel data analysis method for multicolour flow cytometry links variability of multiple markers on single cells to a clinical phenotype
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/15b0fc1fdf734f5faa8858f42b7ef7f9
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Novel data analysis method for multicolour flow cytometry links variability of multiple markers on single cells to a clinical phenotype

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