Sofie Van Gassen

TL;DR: A new visualization technique is introduced, called FlowSOM, which analyzes Flow or mass cytometry data using a Self‐Organizing Map, using a two‐level clustering and star charts, to obtain a clear overview of how all markers are behaving on all cells, and to detect subsets that might be missed otherwise.

TL;DR: These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community providing the theory and key practical aspects offlow cytometry enabling immunologists to avoid the common errors that often undermine immunological data.

TL;DR: A universal toolbox for the automated identification of DCs through unsupervised analysis of conventional flow cytometry and mass cytometry data obtained from multiple mouse, macaque, and human tissues is provided and validated.

TL;DR: This Review provides non-experts with a broad and practical overview of the many recent developments in computational flow cytometry.

TL;DR: These findings unravel the precise timing of immunological events occurring during a term pregnancy and provide the analytical framework to identify immunological deviations implicated in pregnancy-related pathologies.