Quantifying similarity between highdimensional single cell samples is challenging, and usually requires some simplifying hypothesis to be made. By transforming the high dimensional space into a high dimensional grid, the number of cells in each subspace of the grid is characteristic of a given sample. Using a Hilbert curve each sample can be visualized as a simple density plot, and the distance between samples can be calculated from the distribution of cells using the JensenShannon distance. Bins that correspond to significant differences between samples can identified using a simple bootstrap procedure.
Package details 


Author  Yann Abraham [aut, cre], Marilisa Neri [aut], John Skilling [ctb] 
Maintainer  Yann Abraham <yann.abraham@gmail.com> 
License  CC BYNCSA 4.0 
Version  0.4.3 
URL  http://github.com/yannabraham/hilbertSimilarity 
Package repository  View on CRAN 
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