doi:10.1093/nar/gkac219>. It is not only computationally efficient and scalable to the sample size increment, but also is capable of choosing the smoothness parameter and the number of clusters as well.">

DR.SC: Joint Dimension Reduction and Spatial Clustering (original) (raw)

Joint dimension reduction and spatial clustering is conducted for Single-cell RNA sequencing and spatial transcriptomics data, and more details can be referred to Wei Liu, Xu Liao, Yi Yang, Huazhen Lin, Joe Yeong, Xiang Zhou, Xingjie Shi and Jin Liu. (2022) <doi:10.1093/nar/gkac219>. It is not only computationally efficient and scalable to the sample size increment, but also is capable of choosing the smoothness parameter and the number of clusters as well.

Version: 3.5
Depends: parallel, spatstat.geom, R (≥ 4.0.0)
Imports: CompQuadForm, irlba, cowplot, ggplot2, GiRaF, MASS, Matrix, mclust, methods, purrr, S4Vectors, RColorBrewer, Rcpp (≥ 1.0.5), Seurat, stats
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown
Published: 2025-03-29
DOI: 10.32614/CRAN.package.DR.SC
Author: Wei Liu [aut, cre], Yi Yang [aut], Jin Liu [aut]
Maintainer: Wei Liu
BugReports: https://github.com/feiyoung/DR.SC/issues
License: GPL-3
URL: https://github.com/feiyoung/DR.SC
NeedsCompilation: yes
Materials: README
CRAN checks: DR.SC results

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