ArticleScientific reports2017
Novel data analysis method for multicolour flow cytometry links variability of multiple markers on single cells to a clinical phenotype.
Article in Scientific reports, 2017. 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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Who cites it
8 citing papers in PubMed, 25 citations in OpenAlex.
- Analytical Appraisal of Hematogones in B-ALL MRD Assessment Using Multidimensional Dot-Plots by Multiparametric Flow Cytometry: A Critical Review and Update.Indian journal of hematology & blood transfusion : an official journal of Indian Society of Hematology and Blood Transfusion · 2024Review
- Natural killer cell profiles in recurrent pregnancy loss: Increased expression and positive associations with TACTILE and LILRB1.American journal of reproductive immunology (New York, N.Y. : 1989) · 2022Article
- Biomarkers in Different Asthma Phenotypes.Genes · 2021Review
- Flow cytometric evaluation of the neutrophil compartment in COVID-19 at hospital presentation: A normal response to an abnormal situation.Journal of leukocyte biology · 2021Article
- Flow Cytometry: From Experimental Design to Its Application in the Diagnosis and Monitoring of Respiratory Diseases.International journal of molecular sciences · 2020Review
- Multi-set Pre-processing of Multicolor Flow Cytometry Data.Scientific reports · 2020Article
- Key steps and methods in the experimental design and data analysis of highly multi-parametric flow and mass cytometry.Computational and structural biotechnology journal · 2020Review
- A novel data fusion method for the effective analysis of multiple panels of flow cytometry data.Scientific reports · 2019Article
Corrections and comments
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Authors and funding
10 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.