Package: coFAST 0.2.0

Wei Liu

coFAST: Spatially-Aware Cell Clustering Algorithm with Cluster Significant Assessment

A spatially-aware cell clustering algorithm is provided with cluster significance assessment. It comprises four key modules: spatially-aware cell-gene co-embedding, cell clustering, signature gene identification, and cluster significant assessment. More details can be referred to Peng Xie, et al. (2025) <doi:10.1016/j.cell.2025.05.035>.

Authors:Wei Liu [aut, cre], Xiao Zhang [aut], Yi Yang [aut], Peng Xie [aut], Chengqi Lin [aut], Jin Liu [aut]

coFAST_0.2.0.tar.gz
coFAST_0.2.0.zip(r-4.7)coFAST_0.2.0.zip(r-4.6)coFAST_0.2.0.zip(r-4.5)
coFAST_0.2.0.tgz(r-4.6-x86_64)coFAST_0.2.0.tgz(r-4.6-arm64)coFAST_0.2.0.tgz(r-4.5-x86_64)coFAST_0.2.0.tgz(r-4.5-arm64)
coFAST_0.2.0.tar.gz(r-4.7-arm64)coFAST_0.2.0.tar.gz(r-4.7-x86_64)coFAST_0.2.0.tar.gz(r-4.6-arm64)coFAST_0.2.0.tar.gz(r-4.6-x86_64)
coFAST_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
coFAST/json (API)

# Install 'coFAST' in R:

install.packages('coFAST', repos = c('https://feiyoung.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/feiyoung/cofast/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

Datasets:

CosMx_subset - A CosMix spatial transcriptomics data
pbmc3k_subset - A toy single-cell RNA-seq data
top5_signatures - A dataframe including top five signature genes

On CRAN:

openblas cpp

4.00 score 150 downloads 12 exports 229 dependencies

Last updated from:4232715b09. Checks:12 OK, 1 ERROR. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	402
linux-devel-x86_64	OK	428
source / vignettes	OK	403
linux-release-arm64	OK	464
linux-release-x86_64	OK	527
macos-release-arm64	OK	303
macos-release-x86_64	OK	539
macos-oldrel-arm64	ERROR	265
macos-oldrel-x86_64	OK	705
windows-devel	OK	447
windows-release	OK	351
windows-oldrel	OK	346
wasm-release	OK	320

Exports:AddAdj AddCluster Addcoord2embed AggregationScore coembed_plot coembedding_umap coFAST diagnostic.cor.eigs find.signature.genes get.top.signature.dat NCFM pdistance

Dependencies:abind ade4 askpass assorthead backports base64enc beachmat beeswarm BH Biobase BiocGenerics BiocNeighbors BiocParallel BiocSingular bitops boot broom bslib cachem Cairo car carData caTools cli cluster codetools colorspace commonmark CompQuadForm corrplot cowplot cpp11 crayon crosstalk curl data.table DelayedArray deldir Deriv digest doBy dotCall64 dplyr dqrng DR.SC evaluate farver fastDummies fastmap fitdistrplus FNN fontawesome forecast formatR Formula fracdiff fs furrr futile.logger futile.options future future.apply generics GenomicRanges ggbeeswarm ggplot2 ggpubr ggrastr ggrepel ggridges ggsci ggsignif ggthemes globals glue goftest gplots gridExtra gtable gtools harmony here highr hms htmltools htmlwidgets httpuv httr ica igraph IRanges irlba isoband jquerylib jsonlite KernSmooth knitr labeling lambda.r later lattice lazyeval lifecycle listenv lme4 lmtest magrittr MASS Matrix MatrixGenerics MatrixModels matrixStats mclust memoise mgcv microbenchmark mime miniUI minqa modelr nlme nloptr nnet numDeriv openssl otel parallelly patchwork pbapply pbkrtest pheatmap pillar pixmap pkgconfig plotly plyr png polyclip polynom PRECAST prettyunits ProFAST progress progressr promises purrr quantreg R6 ragg RANN rappdirs rbibutils RColorBrewer Rcpp RcppAnnoy RcppArmadillo RcppEigen RcppHNSW RcppML RcppProgress RcppTOML Rdpack reformulas reshape2 reticulate RhpcBLASctl rlang rmarkdown ROCR rprojroot RSpectra rstatix rsvd Rtsne S4Arrays S4Vectors S7 sass ScaledMatrix scales scater scattermore sctransform scuttle Seqinfo Seurat SeuratObject shiny SingleCellExperiment sitmo snow sourcetools sp spam SparseArray SparseM spatstat.data spatstat.explore spatstat.geom spatstat.random spatstat.sparse spatstat.univar spatstat.utils stringi stringr SummarizedExperiment survival sys systemfonts tensor textshaping tibble tidyr tidyselect timeDate tinytex urca utf8 uwot vctrs vipor viridis viridisLite withr xfun xtable XVector yaml zoo

coFAST: NSCLC CosMx data coembedding

Wei Liu

Rendered fromCosMx.Rmdusingknitr::rmarkdownon May 30 2026.

Last update: 2025-11-17
Started: 2025-03-14

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Calculate the adjacency matrix given a spatial coordinate matrix	AddAdj
Find clusters for SRT data	AddCluster
Add the spatial coordinates to the reduction slot	Addcoord2embed
Calculate the aggregation score for specific clusters	AggregationScore
Coembedding dimensional reduction plot	coembed_plot
Calculate UMAP projections for coembedding of cells and features	coembedding_umap
Cell-feature coembedding for SRT data	coFAST
A CosMix spatial transcriptomics data	CosMx_subset
Determine the dimension of low dimensional embedding	diagnostic.cor.eigs diagnostic.cor.eigs.default diagnostic.cor.eigs.Seurat
Find the signature genes for each group of cell/spots	find.signature.genes
Obtain the top signature genes and related information	get.top.signature.dat
Cell-feature coembedding for scRNA-seq data	NCFM
A toy single-cell RNA-seq data	pbmc3k_subset
Calculate the cell-feature distance matrix	pdistance
A dataframe including top five signature genes	top5_signatures