FLOOD: FLow cytometric Orthogonal Orientation for Diagnosis

• We present a novel method for the analysis of Multicolour Flow Cytometry data that uses concepts from the NOC approach in industrial process monitoring
• The method may simultaneously diagnose immunological responses from the multivariate distributions of surface marker expressions on immunological cells.
• The model may reveal the underlying immunological response mechanisms from the response-associated multivariate patterns of variability.
• The method may thirdly identify the specific single cells that are associated to the response.

Multicolour Flow Cytometry (MFC) is widely used for single-cell analysis and employs a vastly increasing number of markers. It can be used for disease diagnosis, research of disease mechanisms and the identification and isolation of individual cells based on their surface marker profile. However, data analysis methods exploiting all these advantages are lacking. Our novel FLow cytometric Orthogonal Orientation for Diagnosis (FLOOD) method reveals disease specific marker patterns. The method constructs a benchmark from surface marker abundances that is used to highlight deviations of challenged from unchallenged individuals. We demonstrate its power in an in vivo study of the response of healthy humans to lipopolysaccharide (LPS) challenge. FLOOD reveals a reproducible pattern of challenge specific markers on blood neutrophils. The method both provides new mechanistic insights and confirms established knowledge on LPS-response, which demonstrates the high potential of FLOOD for both clinical and research application.