CytoCompare: an R Package for Computational Comparisons of Cytometry Profiles

Cytometry is an experimental technique used to measure molecules expressed by cells at a single cell resolution. Recently, several technological improvements have made possible to greatly increase the number of cell markers that can be simultaneously measured. Many computational methods have been proposed to identify clusters of cells having similar phenotypes.

Nevertheless, very few computational method exists to compare the phenotypes of cell clusters identified by different clustering approaches. These phenotypic comparisons are necessary to choose the appropriate clustering methods and settings. Because of this lack of computational tools, comparisons of cell cluster phenotypes are often performed manually, a highly biased and time-consuming process.

CytoCompare is an R package that performs comparisons between the phenotypes of cell clusters with the purpose of identifying similar ones. For each comparison of two cell clusters, CytoCompare provides a distance measure as well as a p-value asserting the statistical significance of the phenotypical difference CytoCompare can generate parallel coordinates, parallel heatmaps, multidimensional scaling or circular graph representations to visualize easily cell cluster phenotypes and the comparison results. CytoCompare can import clustering results from various algorithms including SPADE, viSNE/ACCENSE, and Citrus, the most current widely used algorithms.

References

https://github.com/tchitchek-lab/CytoCompare

A Computational Approach for Phenotypic Comparisons of Cell Populations in High-Dimensional Cytometry Data https://doi.org/10.1016/j.ymeth.2017.09.005