Unsupervised flow cytometry analysis in hematological malignancies: A new paradigm
نویسندگان
چکیده
Ever since hematopoietic cells became “events” enumerated and characterized in suspension by cell counters or flow cytometers, researchers engineers have strived to refine the acquisition display of electronic signals generated. A large array solutions was then developed identify at best numerous subsets that can be delineated, notably among cells. As instruments more stable robust, focus moved analytic software. Almost concomitantly, capacity increased use panels (both with mass classical cytometry) apply artificial intelligence/machine learning for their analysis. The combination these concepts raised new analytical possibilities, opening an unprecedented field subtle exploration many conditions, including hematopoiesis hematological disorders. In this review, general progress achieved development approaches exploring high-dimensional data sets single-cell level will described as they appeared over past few years. larger practical part detail various steps need mastered, both preanalytical check files. Finally, a step-by-step explanation solution combine Bioconductor clustering algorithm FlowSOM popular widely used software Kaluza® (Beckman Coulter) presented. aim review point out day when progresses reach routine hematology laboratories does not seem so far away.
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ژورنال
عنوان ژورنال: International Journal of Laboratory Hematology
سال: 2021
ISSN: ['1751-553X', '1751-5521']
DOI: https://doi.org/10.1111/ijlh.13548