PRECAST: Embedding and Clustering with Alignment for Spatial Datasets (original) (raw)
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 |
| BugReports: | https://github.com/feiyoung/PRECAST/issues |
| License: | GPL-3 |
| URL: | https://github.com/feiyoung/PRECAST |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | PRECAST results |
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