Por favor, use este identificador para citar o enlazar a este item:
http://hdl.handle.net/10261/219672
COMPARTIR / EXPORTAR:
SHARE CORE BASE | |
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE | |
Título: | From big flow cytometry datasets to smart diagnostic strategies: The EuroFlow approach |
Autor: | Pedreira, C. E.; Sobral da Costa, E.; Lécrevisse, Quentin; Grigore, Georgiana Emilia; Fluxá, Rafael; Verde, Javier; Hernández, Juan; Dongen, J. J. M. van; Orfao, Alberto CSIC ORCID | Fecha de publicación: | 2019 | Editor: | Elsevier | Citación: | Journal of Immunological Methods 475: 112631 (2019) | Resumen: | The rise in the analytical speed of mutiparameter flow cytometers made possible by the introduction of digital instruments, has brought up the possibility to manage progressively higher number of parameters simultaneously on significantly greater numbers of individual cells. This has led to an exponential increase in the complexity and volume of flow cytometry data generated about cells present in individual samples evaluated in a single measurement. This increase demands for new developments in flow cytometry data analysis, graphical representation, and visualization and interpretation tools to address the new big data challenges, i.e. processing data files of ≥10–25 parameters per cell in samples with >5–10 million cells (= up to 250 million data points per cell sample) obtained in a few minutes. Here, we present a comprehensive review of some of the tools developed by the EuroFlow consortium for processing flow cytometric big data files in diagnostic laboratories, particularly focused on automated EuroFlow approaches for: i) identification of all cell populations coexisting in a sample (automated gating); ii) smart classification of aberrant cell populations in routine diagnostics; iii) automated reporting; together with iv) new tools developed to visualize n-dimensional data in 2-dimensional plots to support expert-guided automated data analysis. The concept of using reference data bases implemented into software programs, in combination with multivariate statistical analysis pioneered by EuroFlow, provides an innovative, highly efficient and fast approach for diagnostic screening, classification and monitoring of patients with distinct hematological and immune disorders, as well as other diseases. | Descripción: | On behalf of EuroFlow. | Versión del editor: | https://doi.org/10.1016/j.jim.2019.07.003 | URI: | http://hdl.handle.net/10261/219672 | DOI: | 10.1016/j.jim.2019.07.003 | ISSN: | 0022-1759 |
Aparece en las colecciones: | (IBMCC) Artículos |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
---|---|---|---|---|
accesoRestringido.pdf | 59,24 kB | Adobe PDF | Visualizar/Abrir |
CORE Recommender
SCOPUSTM
Citations
30
checked on 26-mar-2024
WEB OF SCIENCETM
Citations
30
checked on 12-feb-2024
Page view(s)
129
checked on 29-mar-2024
Download(s)
126
checked on 29-mar-2024
Google ScholarTM
Check
Altmetric
Altmetric
NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.