StImage is a R package for integrated analysis of spatial transcriptomics and the corresponding modality images. StImage is freely available at https://github.com/YuWang-VUMC/stImage.
Before installing stImage, dependencies should be installed first:
# SPARK/SPARKX and SpatialPCA
library(devtools)
install_github('xzhoulab/SPARK')
install_github("shangll123/SpatialPCA")
#BioConductor packages
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install(c("rhdf5", "SingleCellExperiment", "BayesSpace", "omicade4"))
Users should also make sure to successfully install the tensorflow and keras following instruction Tensorflow for R.
#installation of tensorflow
install.packages("tensorflow")
#create python virtualenv. If already installed python, replace 'install_python()' with the path of excutable python.
library(reticulate)
path_to_python <- install_python()
virtualenv_create("r-reticulate", python = path_to_python)
library(tensorflow)
install_tensorflow(envname = "r-reticulate")
#installation of keras
install.packages("keras")
library(keras)
install_keras(envname = "r-reticulate")
#testing the installation
library(tensorflow)
tf$constant("Hello Tensorflow!")
Once Tensorflow and keras were successfully installed, you can then install the latest version of stImage from GitHub with:
library(devtools)
install_github("YuWang-VUMC/stImage")
The tutorial includes main example codes for multiple spatial transcriptomics datasets (e.g. Adult Mouse Olfactory Bulb and Human breast tumor)
stImage is licensed under the MIT License.
stImage xxx.
doi: xxx