# PRECAST: installation

## Install the PRECAST

This vignette provides an introduction to the R package `PRECAST`, where the function `PRECAST` implements the model `PRECAST`, a PRobabilistic Embedding and Clustering with alignment for Spatial Transcriptomics data integration . The package can be installed with the following command from Github:

`install.packages('remotes')` `remotes::install_github("feiyoung/PRECAST")`

or install from CRAN

`install.packages("PRECAST")`

The package can be loaded with the command:

    library("PRECAST")
    #> Loading required package: parallel
    #> Loading required package: gtools
    #> Warning: package 'gtools' was built under R version 4.2.2
    #> The legacy packages maptools, rgdal, and rgeos, underpinning the sp package,
    #> which was just loaded, will retire in October 2023.
    #> Please refer to R-spatial evolution reports for details, especially
    #> https://r-spatial.org/r/2023/05/15/evolution4.html.
    #> It may be desirable to make the sf package available;
    #> package maintainers should consider adding sf to Suggests:.
    #> The sp package is now running under evolution status 2
    #>      (status 2 uses the sf package in place of rgdal)
    #> PRECAST :  An efficient data integration method is provided for multiple spatial transcriptomics data with non-cluster-relevant effects such as the complex batch effects. It unifies spatial factor analysis simultaneously with spatial clustering and embedding alignment, requiring only partially shared cell/domain clusters across datasets. More details can be referred to Wei Liu, et al. (2023) <doi:10.1038/s41467-023-35947-w>.   Check out our Package website (https://feiyoung.github.io/PRECAST/index.html) for a more complete description of the methods and analyses

## Setup on Linux or MacOS system

For running big data, users can use the following system command to set the C_stack unlimited in case of `R Error: C stack usage is too close to the limit`.

    ulimit -s unlimited