Discussion

Traditional flow cytometry analysis is biased by personal judgment at each stage of the analysis. Gates are drawn to include and exclude cells based on the expected expression pattern of the antigens. The analysis often focusses on subsets of cells which an investigator deems to be important, resulting in the exclusion of other subsets which may in fact have biological significance.

SPADE (Spanning-tree Progression Analysis of Density-normalized Events) analysis is an attempt at an unbiased approach to flow cytometry analysis. The software was developed to enable the analysis of Cytoff data but is equally applicable to fluorescent flow cytometry data. SPADE analysis is a clustering protocol which groups the cells into populations (termed “nodes”) based on their expression of specific markers, building a map of cellular populations. Such an approach should enable faster analysis and reduce the likelihood of small populations of cells which express the antigen being overlooked by the analysis. The recently described innate lymphoid cells are a good example of this.

In the work presented here, SPADE analysis was performed to investigate the expression of CCR4 in myeloid cells in the peripheral blood of healthy donors. Traditional analysis carried out in parallel failed to identify the expression of CCR4 on a CD141+ monocytic population, and the SPADE analysis also identified some unknown populations of CCR4high cells, the phenotype of which will need to be investigated in future.

Applying this unbiased approach to our flow analysis in future should enable us to better understand the relationships between cell types in health and disease.