knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
The spatialDE package provides an R wrapper for the Python SpatialDE library,
using r BiocStyle::CRANpkg("reticulate")
and r BiocStyle::Biocpkg("basilisk")
.
SpatialDE, by Svensson et al., 2018, is a method to identify spatially variable genes (SVGs) in spatially resolved transcriptomics data.
This package started as part of the BiocSpatialChallenges.
Get the latest stable R
release from CRAN. Then
install r BiocStyle::Biocpkg("spatialDE")
from
Bioconductor using the following code:
if (!requireNamespace("BiocManager", quietly = TRUE)) { install.packages("BiocManager") } BiocManager::install("spatialDE")
The development version of spatialDE can be installed from GitHub with:
if (!requireNamespace("BiocManager", quietly = TRUE)) { install.packages("BiocManager") BiocManager::install("sales-lab/spatialDE")
library(spatialDE) spe <- mockSVG(return_SPE = TRUE) de_results <- spatialDE(spe) head(de_results)
Below is the citation output from using citation('spatialDE')
in R. Please
run this yourself to check for any updates on how to cite spatialDE.
Please note that this package merely provides a wrapper to use the original Python methods in R. If you find these methods useful, please also consider citing the original paper.
print(citation('spatialDE'), bibtex = TRUE)
Please note that the spatialDE project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
r BiocStyle::Biocpkg("SpatialExperiment")
This package was developed using r BiocStyle::Biocpkg('biocthis')
.
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