Movatterモバイル変換


[0]ホーム

URL:


Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

Sign up
Appearance settings

coFAST is a spatially-aware cell clustering algorithm with cluster significant assessment.

NotificationsYou must be signed in to change notification settings

feiyoung/coFAST

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

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

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 ourCell paper, andPackage 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

Please see our new paper for more details:

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 asscater) 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 thevignettes 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, downloadRtools; second, add the Rtools directory to the environment variable.

Setup on MacOS system

First, install Xcode. Installation about Xcode can be referredhere.

Second, install "gfortran" for compiling C++ and Fortran athere.

Setup on Linux system

If you use conda environment on Linux system and some dependent packages (such asscater) can not normally installed, you can search R package at anaconda.org website. We take thescater package as example, and its search result ishttps://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 asscater) 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 asDR.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 functioncoembedding_umap(), user may meet the error: "useNames = NA is defunct. Instead, specify either useNames = TRUE or useNames = FALSE".Because thematrixStats R package remove the argument "useNames=NA" and change the warning to error. Thus, user can install the old version ofmatrixStats 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 ourPackage Website for a demonstration and overview of the functions included in coFAST.

NEWs

  • coFAST version 0.2.0 (2025-12-14):Resolve the issue stemming from the deprecatedslot parameter in theGetAssayData() function within theSeuratObject package.

  • coFAST version 0.1.0 (2025-03-14)

About

coFAST is a spatially-aware cell clustering algorithm with cluster significant assessment.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages


[8]ページ先頭

©2009-2025 Movatter.jp