=========================================================================

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 Package Website 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

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")

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:

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.

Setup on MacOS system

First, install Xcode. Installation about Xcode can be referred here.

Second, install “gfortran” for compiling C++ and Fortran at here.

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 for a demonstration and overview of the functions included in coFAST.

NEWs

  • coFAST version 0.1.0 (2025-03-14)