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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
DOI: 10.32614/CRAN.package.PRECAST
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:

Please use the canonical form https://CRAN.R-project.org/package=PRECAST to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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