Package: hilbertSimilarity
Type: Package
Title: Hilbert Similarity Index for High Dimensional Data
Version: 0.4.4
Date: 2026-01-05
Authors@R: c(person('Yann','Abraham',email='yann.abraham@gmail.com',role=c('aut','cre')),
             person('Marilisa','Neri',email='marilisa.neri@gmail.com',role='aut'),
             person('John','Skilling',role='ctb'))
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.
LinkingTo: Rcpp
Imports: Rcpp, entropy
Suggests: knitr, rmarkdown, ggplot2, dplyr, tidyr, reshape2,
        bodenmiller, abind
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/yannabraham/hilbertSimilarity
BugReports: https://github.com/yannabraham/hilbertSimilarity/issues
VignetteBuilder: knitr
RoxygenNote: 7.3.2
NeedsCompilation: yes
Packaged: 2026-01-13 19:15:25 UTC; yannabraham
Author: Yann Abraham [aut, cre],
  Marilisa Neri [aut],
  John Skilling [ctb]
Maintainer: Yann Abraham <yann.abraham@gmail.com>
Repository: CRAN
Date/Publication: 2026-01-14 08:00:27 UTC
Built: R 4.6.0; x86_64-w64-mingw32; 2026-02-19 02:37:16 UTC; windows
Archs: x64
