CRAN/E | hilbertSimilarity

hilbertSimilarity

Hilbert Similarity Index for High Dimensional Data

Installation

About

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.

github.com/yannabraham/hilbertSimilarity
Bug report File report

Key Metrics

Version 0.4.3
Published 2019-11-11 1765 days ago
Needs compilation? yes
License CC BY-NC-SA 4.0
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Maintainer

Maintainer

Yann Abraham

Authors

Yann Abraham

aut / cre

Marilisa Neri

aut

John Skilling

ctb

Material

README
Reference manual
Package source

Vignettes

Comparing Samples using hilbertSimilarity
Identifying Treatment effects using hilbertSimilarity

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

hilbertSimilarity archive

Imports

Rcpp
entropy

Suggests

knitr
rmarkdown
ggplot2
dplyr
tidyr
reshape2
bodenmiller
abind

LinkingTo

Rcpp