SPADE
SPADE is a clustering algorithm, with clustering performed after down-sampling of events to allow identification of low-density clusters. The algorithm then displays the relatedness of clusters via a dendogram. This "tree" can then be colored by expression level of any given marker, or by fold-change of any marker over control.
Caveats of SPADE include that its result is highly dependent on the settings (initial file gating, down-sampling percentage, target cluster number, and markers used for clustering). Even with the same settings, multiple SPADE runs will result in somewhat different trees, due to the random nature of down-sampling. Tips include:
-Pre-gate your files to at least eliminate debris, doublets, and dead cells.
-Use only a minimal set of markers for clustering, and make sure they are well-resolved. Clustering on very dim markers is dangerous.
-Perform multiple SPADE runs to gain confidence in the analysis.
References
1. Simonds, E. F., Bendall, S. C., Gibbs, K. D., Bruggner, R. V., Linderman, M. D., Sachs, K., et al. (2011). Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE. Nature Biotechnology, 1–8. doi:10.1038/nbt.1991
2. Bendall, S. C., Simonds, E. F., Qiu, P., Amir, E. A. D., Krutzik, P. O., Finck, R., et al. (2011). Single-Cell Mass Cytometry of Differential Immune and Drug Responses Across a Human Hematopoietic Continuum. Science, 332(6030), 687–696. doi:10.1126/science.1198704
3. Bodenmiller, B., Zunder, E. R., Finck, R., Chen, T. J., Savig, E. S., Bruggner, R. V., et al. (2012). Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators. Nature Biotechnology, 30(9), 857–866. doi:10.1038/nbt.2317
4. Horowitz, A., Strauss-Albee, D. M., Leipold, M., Kubo, J., Nemat-Gorgani, N., Dogan, O. C., et al. (2013). Genetic and environmental determinants of human NK cell diversity revealed by mass cytometry. Science Translational Medicine, 5(208), 208ra145. doi:10.1126/scitranslmed.3006702