PRECAST: a probabilistic embedding and clustering with alignment for spatial transcriptomics data integration.
PRECAST is a package for integrating and analyzing multiple spatially resolved transcriptomics (SRT) datasets, developed by the Jin Liu’s lab. It unifies spatial factor analysis simultaneously with spatial clustering and embedding alignment, requiring only partially shared cell/domain clusters across datasets.
Check out our bioRxiv paper for a more complete description of the methods and analyses.
PRECAST can be used to compare and contrast experimental datasets in a variety of contexts, for instance:
Once multiple datasets are integrated, the package provides functionality for further data exploration, analysis, and visualization. Users can:
“PRECAST” depends on the ‘Rcpp’ and ‘RcppArmadillo’ package, which requires appropriate setup of computer. For the users that have set up system properly for compiling C++ files, the following installation command will work.
# Method 1: install PRECAST from CRAN install.packages('PRECAST') # Method 2: Install PRECAST from Github if (!require("remotes", quietly = TRUE)) install.packages("remotes") remotes::install_github("feiyoung/PRECAST") # If some dependent packages (such as `scater`) on Bioconductor can not be installed nomrally, use following commands, then run abouve command. if (!require("BiocManager", quietly = TRUE)) ## install BiocManager install.packages("BiocManager") # install the package on Bioconducter BiocManager::install(c("scater"))
For usage examples and guided walkthroughs, check the
vignettes directory of the repo.
For the users that don’t have set up system properly, the following setup on different systems can be referred. ## Setup on Windows system First, download Rtools; second, add the Rtools directory to the environment variable. Users can follow here to add Windows PATH Environment Variable.
First, install Xcode. Installation about Xcode can be referred here.
Second, install “gfortran” for compiling C++ and Fortran at here.
If you use conda environment on Linux system and some dependent packages (such as
scater) can not normally installed, you can search R package at anaconda.org website. We take the
scater package as example, and its search result is https://anaconda.org/bioconda/bioconductor-scater. Then you can install it in conda environment by following command.
conda install -c bioconda bioconductor-scater
For the user not using conda environment, if dependent packages (such as
scater) not normally installed are in Bioconductor, then use the following command to install the dependent packages.
# install BiocManager if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") # install the package on Bioconducter BiocManager::install(c("scater"))
If dependent packages (such as
DR.SC) not normally installed are in CRAN, then use the following command to install the dependent packages.
# install the package on CRAN install.packages("DR.SC")
For an example of typical PRECAST usage, please see our Package Website for a demonstration and overview of the functions included in PRECAST.