Novel data analysis method for multicolour flow cytometry links variability of multiple markers on single cells to a clinical phenotype

Abstract

Multicolour Flow Cytometry (MFC) produces multidimensional analytical data on the quantitative expression of multiple markers on single cells. This data contains invaluable biomedical information on (1) the marker expressions per cell, (2) the variation in such expression across cells, (3) the variability of cell marker expression across samples that (4) may vary systematically between cells collected from donors and patients. Current conventional and even advanced data analysis methods for MFC data explore only a subset of these levels. The Discriminant Analysis of MultiAspect CYtometry (DAMACY) we present here provides a comprehensive view on health and disease responses by integrating all four levels. We validate DAMACY by using three distinct datasets: in vivo response of neutrophils evoked by systemic endotoxin challenge, the clonal response of leukocytes in bone marrow of acute myeloid leukaemia (AML) patients, and the complex immune response in blood of asthmatics. DAMACY provided good accuracy 91–100% in the discrimination between health and disease, on par with literature values. Additionally, the method provides figures that give insight into the marker expression and cell variability for more in-depth interpretation, that can benefit both physicians and biomedical researchers to better diagnose and monitor diseases that are reflected by changes in blood leukocytes.

Multi-set Pre-processing of Multicolor Flow Cytometry Data

“…Analysis of Multi-Aspect Cytometry (DAMACY) 11 to explore the different pre-processing options mentioned in the method section. DAMACY 11 first describes the cellular variability in N-dimensional histograms based on Simultaneous Component Analysis (SCA) of the pre-processed data using the multi-set structure.…”

“…The multi-set-structure has already been an integral part of the methods DAMACY 11 and ECLIPSE 12 . Both DAMACY and ECLIPSE consider the multi-set structure during the pre-processing steps and when building the models to compare samples.…”

New advances in microfluidic flow cytometry

“…Tinnevelt et al. presented a multivariate method called Discriminant Analysis of MultiAspect CYtometry (DAMACY) to quantitatively compare the leukocyte compositions of multiple individuals. An accuracy 91–100% in the discrimination between health and disease can be achieved by DAMACY.…”

A novel data fusion method for the effective analysis of multiple panels of flow cytometry data

“…One of our recently developed methods, DAMACY, visualises the over- and underrepresented cells in an immune response measured in a case-control experiment 6 . This technique first creates a multidimensional histogram for each sample within a low-dimensional principal component space, which are then quantitatively compared between individuals in a second step using the discriminant analysis method Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA).…”

“…The original implementation of DAMACY focussed on single-panel experiments; however, with relatively small adjustments, the second step involving the quantitative comparison of different histograms can be modified to allow the integration of data from multiple panels measured in the same samples 6 . We can extend the discriminative step of DAMACY to incorporate the fusion of data from multiple measured aliquots to discern groups of samples based on the covariance between the cell populations they express within each panel, and the relationships between the cell populations in the different panels.…”