Package: hilbertSimilarity
Type: Package
Title: Hilbert Similarity Index for High Dimensional Data
Version: 0.4.3
Date: 2019-11-11
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: CC BY-NC-SA 4.0
LazyData: TRUE
Encoding: UTF-8
URL: http://github.com/yannabraham/hilbertSimilarity
BugReports: http://github.com/yannabraham/hilbertSimilarity/issues
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-11-11 15:06:56 UTC; ayann
Author: Yann Abraham [aut, cre],
  Marilisa Neri [aut],
  John Skilling [ctb]
Maintainer: Yann Abraham <yann.abraham@gmail.com>
Repository: CRAN
Date/Publication: 2019-11-11 23:50:02 UTC
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