coFAST

# coFAST


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coFAST is a spatially-aware cell clustering algorithm with cluster significant assessment. It comprises four key modules: spatially-aware cell-gene co-embedding, cell clustering, signature gene identification, and cluster significant assessment.

Check out  our our [Cell paper](https://doi.org/10.1016/j.cell.2025.05.035), and [Package Website](https://feiyoung.github.io/coFAST/index.html) for a more complete description of the methods and analyses. 


Once the coembeddings of  dataset are estimated by coFAST, the package provides functionality for further data exploration, 
analysis, and visualization. Users can:

* Conduct Spatially-aware clustering
* Find the signature genes 
* Visuzlize the coembeddings on UMAP space
* Visuzlize the signature genes on UMAP space


Please see our new paper for more details:

- [Peng Xie^c, Juan Shen^c, Yi Yang^c, Xinrui Wang^c, Wei Liu^c, Hailong Cao^c, Yanying Zheng, Chen Wu, Guangyao Mao, Linjin Chen, Jingjing He, Weiheng Zheng, Zepu Yang, Xiao Zhang, Xu Jiang, Xianfa Yang, Ke Fang, Zhao Zhang, Xin Xue, Xueting Chen, Chaoyi Wang, Xing Liu, Lin Liu, Xuebiao Yao, Naihe Jing, Wei Xie, Jin Liu*, Hua Cao*, Zhuojuan Luo*, Xiaodong Fang*, Chengqi Lin*  (2025), Digital reconstruction of full embryos during early mouse organogenesis. Cell.](https://doi.org/10.1016/j.cell.2025.05.035)


# Installation
"coFAST" 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.




    if (!require("remotes", quietly = TRUE))
    install.packages("remotes")
    
    remotes::install_github("feiyoung/coFAST")

Or install the the packages "coFAST" from 'CRAN'

   
   install.packages("coFAST")
 


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"))




## Usage
For usage examples and guided walkthroughs, check the `vignettes` directory of the repo. 

Tutorials for coFAST method:

* [SRT data analysis for NSCLC](https://feiyoung.github.io/coFAST/articles/CosMx.html)



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](https://cran.r-project.org/bin/windows/Rtools/); second, add the Rtools directory to the environment variable.


## Setup on MacOS system
First, install Xcode. Installation about Xcode can be referred [here](https://stackoverflow.com/questions/8291146/xcode-installation-on-mac).


Second, install "gfortran" for compiling C++ and Fortran at [here](https://github.com/fxcoudert/gfortran-for-macOS).


## Setup on Linux  system
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")



## Common errors
* When using function `coembedding_umap()`, user may meet the error: "useNames = NA is defunct. Instead, specify either useNames = TRUE or useNames = FALSE".
Because the `matrixStats` R package remove the argument "useNames=NA" and change the warning to error. Thus, user can install the old version of `matrixStats` by the following code

all old versions that are less than 1.1.0  are ok.
here we take the version 1.1.0 as an example.
    
    remotes::install_version('matrixStats', version='1.1.0') 



# Demonstration

For an example of typical coFAST usage, please see our [Package Website](https://feiyoung.github.io/coFAST/index.html) for a demonstration and overview of the functions included in coFAST.

# NEWs
* coFAST version 0.1.0 (2025-03-14)