PRECAST: Embedding and Clustering with Alignment for Spatial Datasets

An efficient data integration method is provided for multiple spatial transcriptomics data with non-cluster-relevant effects such as the complex batch effects. It unifies spatial factor analysis simultaneously with spatial clustering and embedding alignment, requiring only partially shared cell/domain clusters across datasets. More details can be referred to Wei Liu, et al. (2023) <doi:10.1038/s41467-023-35947-w>.

Version:	1.6.5
Depends:	parallel, gtools, R (≥ 4.0.0)
Imports:	GiRaF, MASS, Matrix, mclust, methods, purrr, utils, Seurat, cowplot, patchwork, scater, pbapply, ggthemes, dplyr, ggplot2, stats, DR.SC, scales, ggpubr, graphics, colorspace, Rcpp (≥ 1.0.5)
LinkingTo:	Rcpp, RcppArmadillo
Suggests:	knitr, rmarkdown
Published:	2024-03-19
Author:	Wei Liu [aut, cre], Yi Yang [aut], Jin Liu [aut]
Maintainer:	Wei Liu <liuweideng at gmail.com>
BugReports:	https://github.com/feiyoung/PRECAST/issues
License:	GPL-3
URL:	https://github.com/feiyoung/PRECAST
NeedsCompilation:	yes
Materials:	README
CRAN checks:	PRECAST results

Documentation:

Reference manual:	PRECAST.pdf
Vignettes:	PRECAST: Human Breast Cancer Data Analysis PRECAST: DLPFC Single Sample Analysis PRECAST: Four DLPFC Sample Analysis PRECAST PRECAST: simulation

Downloads:

Package source:	PRECAST_1.6.5.tar.gz
Windows binaries:	r-devel: PRECAST_1.6.5.zip, r-release: PRECAST_1.6.5.zip, r-oldrel: PRECAST_1.6.5.zip
macOS binaries:	r-release (arm64): PRECAST_1.6.5.tgz, r-oldrel (arm64): PRECAST_1.6.5.tgz, r-release (x86_64): PRECAST_1.6.5.tgz, r-oldrel (x86_64): PRECAST_1.6.5.tgz
Old sources:	PRECAST archive

Reverse dependencies:

Reverse imports:

ProFAST

Linking:

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