Spatial analysis of in situ cytometry data.
The spicyR package provides a framework for performing inference on changes in spatial relationships between pairs of cell types for cell-resolution spatial omics technologies. spicyR consists of three primary steps: (i) summarizing the degree of spatial localization between pairs of cell types for each image; (ii) modelling the variability in localization summary statistics as a function of cell counts and (iii) testing for changes in spatial localizations associated with a response variable.
For the Bioconductor release version, run the following.
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("spicyR")If you would like the most up-to-date features, install the most recent development version.
# Install the development version from Bioconductor:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
# This will update all your Bioconductor packages to devel version
BiocManager::install(version='devel')
BiocManager::install("spicyR")
# Otherwise install the development version from GitHub:
# install.packages("devtools")
devtools::install_github("ellispatrick/spicyR")
library(spicyR)spicyR is still under active development. We would greatly appreciate any and
all feedback related to the package.
- R package related issues should be raised here.
- For general questions and feedback, please contact us directly via ellis.patrick@sydney.edu.au.
- Nicolas Canete
- Ellis Patrick - @TheEllisPatrick
Nicolas P Canete, Sourish S Iyengar, John T Ormerod, Heeva Baharlou, Andrew N Harman, Ellis Patrick, spicyR: spatial analysis of in situ cytometry data in R, Bioinformatics, Volume 38, Issue 11, 1 June 2022, Pages 3099–3105, https://doi.org/10.1093/bioinformatics/btac268