yannabraham/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.

Getting started

Package details

Maintainer
LicenseCC BY-NC-SA 4.0
Version0.4
URL http://github.com/yannabraham/hilbertSimilarity
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("yannabraham/hilbertSimilarity")
yannabraham/hilbertSimilarity documentation built on April 20, 2019, 7:17 a.m.