Quantifying similarity between high-dimensional 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 sub-space 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 Jensen-Shannon distance. Bins that correspond to significant differences between samples can identified using a simple bootstrap procedure.

hilbertSimilarity

hilbertSimilarity is a R package to compute similarity between high dimensional samples, using discretization to summarize data and the Jensen-Shannon distance to compute similarity.

To install hilbertSimilarity

devtools::install_github('yannabraham/hilbertSimilarity')

Or, if you want to build the vignette:

devtools::install_github('yannabraham/hilbertSimilarity',build_vignettes = TRUE)

Travis Build Status

CRAN Version.