Unsupervised Clustering using SPADE

SPADE (Spanning-tree Progression Analysis of Density-normalized Events) is a way to automatically identify populations in multidimensional cytometry data files on the Cytobank platform. SPADE clusters cells into populations and then projects them into a tree like the one shown below 1. SPADE works for data from both ‘classic’ fluorescence flow cytometry and mass cytometry.

Looking at individual SPADE trees for different samples analyzed together. This two tree problem is solved easily in SPADE by overlaying the trees. Each node, instead of displaying a raw value for intensity on a certain channel, will now display a fold intensity. To achieve this, fold change groups need to be defined.

A fold change group is a collection of files that will be compared amongst each other for the fold change calculation. Each file will be compared to a defined baseline file in order to calculate fold change. Multiple baseline files can be selected within one group.

Unsupervised Clustering using SPADE

For more details and instructions also visit our Cytobank Support pages.


  1. Qiu P, Simonds EF, Bendall SC, et al. Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE. Nature Biotechnology. 2011;29(10):886-891. doi:10.1038/nbt.1991