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hilbertSimilarity  

Hilbert Similarity Index for High Dimensional Data
View on CRAN: Click here


Download and install hilbertSimilarity package within the R console
Install from CRAN:
install.packages("hilbertSimilarity")

Install from Github:
library("remotes")
install_github("cran/hilbertSimilarity")

Install by package version:
library("remotes")
install_version("hilbertSimilarity", "0.4.4")



Attach the package and use:
library("hilbertSimilarity")
Maintained by
Yann Abraham
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-11-05
Latest Update: 2019-11-11
Description:
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.
How to cite:
Yann Abraham (2019). hilbertSimilarity: Hilbert Similarity Index for High Dimensional Data. R package version 0.4.4, https://cran.r-project.org/web/packages/hilbertSimilarity. Accessed 10 Mar. 2026.
Previous versions and publish date:
0.4.2 (2019-11-05 10:40), 0.4.3 (2019-11-12 00:50)
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Complete documentation for hilbertSimilarity
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