FCS files from 553 BM aspirates from newly diagnosed MM patients were analyzed using the semi-automated algorithm named “FlowCT” v.0.0.951 (link), which is based on the analysis of multiple files by automated cell clustering. Briefly, FCS files were merged, underwent quality control, were normalized through batch removal steps and clustered using FlowSOM. After the computational clustering, the Infinicyt software v.2.0 (Cytognos SL, Salamanca, Spain) was used for the identification of each cluster. Statistical analysis was then performed based on the output of the software.
Other organizations :
Clinica Universidad de Navarra, Navarre Institute of Health Research, Centro de Investigación Biomédica en Red de Cáncer, University of Palermo, Centro de Investigación del Cáncer, Instituto de Investigación Biomédica de Salamanca, Hospital Universitario 12 De Octubre, University of Milano-Bicocca, Ca' Foscari University of Venice, Ospedale Annunziata di Cosenza, University of Reggio Calabria, Institut Català d'Oncologia, Hospital Universitario De Cabueñes, Institut d'Investigació Biomédica de Bellvitge, Universidad de Murcia, Hospital General Universitario Morales Meseguer, Hospital Universitario Puerta de Hierro Majadahonda, Vall d'Hebron Hospital Universitari, Hospital Universitario de Canarias, Hospital Son Llatzer, Hospital Clínico Universitario Lozano Blesa, Hospital Universitario Son Espases, Institut universitaire du cancer de Toulouse Oncopole, Azienda Socio Sanitaria Territoriale degli Spedali Civili di Brescia, Universidad de Salamanca, Hospital Clínic de Barcelona, Consorci Institut D'Investigacions Biomediques August Pi I Sunyer
The semi-automated algorithm named "FlowCT" v.0.0.9
dependent variables
Output of the Infinicyt software v.2.0 (Cytognos SL, Salamanca, Spain) used for the identification of each cluster
Statistical analysis performed based on the output of the software
control variables
FCS files from 553 BM aspirates from newly diagnosed MM patients
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