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An R-Derived FlowSOM Process to Analyze Unsupervised Clustering of Normal and Malignant Human Bone Marrow Classical Flow Cytometry Data
- Source :
- Cytometry. Part A : the journal of the International Society for Analytical CytologyLiterature Cited. 95(11)
- Publication Year :
- 2019
-
Abstract
- Multiparameter flow cytometry (MFC) is a powerful and versatile tool to accurately analyze cell subsets, notably to explore normal and pathological hematopoiesis. Yet, mostly supervised subjective strategies are used to identify cell subsets in this complex tissue. In the past few years, the implementation of mass cytometry and the big data generated have led to a blossoming of new software solutions. Their application to classical MFC in hematology is however still seldom reported. Here, we show how one of these new tools, the FlowSOM R solution, can be applied, together with the Kaluza® software, to a new delineation of hematopoietic subsets in normal human bone marrow (BM). We thus combined the unsupervised discrimination of cell subsets provided by FlowSOM and their expert-driven node-by-node assignment to known or new hematopoietic subsets. We also show how this new tool could modify the MFC exploration of hematological malignancies both at diagnosis (Dg) and follow-up (FU). This can be achieved by direct comparison of merged listmodes of reference normal BM, Dg, and FU samples of a representative acute myeloblastic case tested with the same immunophenotyping panel. This provides an immediate unsupervised evaluation of minimal residual disease. © 2019 International Society for Advancement of Cytometry.
- Subjects :
- 0301 basic medicine
medicine.medical_specialty
Histology
Neoplasm, Residual
Computer science
Human bone
Bone Marrow Cells
Computational biology
Fluorescence
Pathology and Forensic Medicine
Flow cytometry
Immunophenotyping
03 medical and health sciences
0302 clinical medicine
Bone Marrow
Internal medicine
medicine
Cluster Analysis
Humans
Mass cytometry
B-Lymphocytes
Hematology
Leukemia
medicine.diagnostic_test
Precursor Cells, B-Lymphoid
Cell Biology
Flow Cytometry
Minimal residual disease
030104 developmental biology
medicine.anatomical_structure
030220 oncology & carcinogenesis
Bone marrow
Cytometry
Software
Subjects
Details
- ISSN :
- 15524930
- Volume :
- 95
- Issue :
- 11
- Database :
- OpenAIRE
- Journal :
- Cytometry. Part A : the journal of the International Society for Analytical CytologyLiterature Cited
- Accession number :
- edsair.doi.dedup.....f440de850173e3d7b78bac12b2e7d578