hilbertSimilarity: Hilbert Similarity Index for High Dimensional Data

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.

Package details

AuthorYann Abraham [aut, cre], Marilisa Neri [aut], John Skilling [ctb]
MaintainerYann Abraham <yann.abraham@gmail.com>
LicenseCC BY-NC-SA 4.0
URL http://github.com/yannabraham/hilbertSimilarity
Package repositoryView on CRAN
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hilbertSimilarity documentation built on Nov. 12, 2019, 1:06 a.m.