ProFAST: Probabilistic Factor Analysis for Spatially-Aware Dimension Reduction

Probabilistic factor analysis for spatially-aware dimension reduction across multi-section spatial transcriptomics data with millions of spatial locations. More details can be referred to Wei Liu, et al. (2023) <doi:10.1101/2023.07.11.548486>.

Version: 1.4
Depends: R (≥ 4.0.0), gtools
Imports: Rcpp (≥ 1.0.10), furrr, future, ggplot2, AnnotationDbi, DR.SC, Matrix, mclust, PRECAST, pbapply, biomaRt, irlba,,, Seurat, parallel, harmony, methods, stats, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, performance, nnet, scater, ggrepel, RANN, grDevices
Published: 2024-03-18
DOI: 10.32614/CRAN.package.ProFAST
Author: Wei Liu [aut, cre], Xiao Zhang [aut], Jin Liu [aut]
Maintainer: Wei Liu <liuweideng at>
License: GPL-3
NeedsCompilation: yes
Materials: README
CRAN checks: ProFAST results


Reference manual: ProFAST.pdf
Vignettes: CoFAST: NSCLC CosMx data coembedding
FAST: single DLPFC section
FAST: two DLPFC sections
FAST: simulation
CoFAST: PBMC scRNA-seq data coembedding


Package source: ProFAST_1.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): ProFAST_1.4.tgz, r-release (x86_64): ProFAST_1.4.tgz, r-oldrel (x86_64): not available
Old sources: ProFAST archive


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