SC.MEB: Spatial Clustering with Hidden Markov Random Field using Empirical Bayes

Spatial clustering with hidden markov random field fitted via EM algorithm, details of which can be found in Yi Yang (2021) <doi:10.1101/2021.06.05.447181>. 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: 1.0
Depends: mclust, R (≥ 2.10)
Imports: Rcpp (≥ 1.0.6), SingleCellExperiment, purrr, Matrix, mvtnorm, GiRaF
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown
Published: 2021-07-16
Author: Yi Yang [aut, cre], Xingjie Shi [aut], Jin Liu [aut]
Maintainer: Yi Yang <yygaosansiban at sina.com>
License: GPL-3
NeedsCompilation: yes
CRAN checks: SC.MEB results

Downloads:

Reference manual: SC.MEB.pdf
Vignettes: SC-MEB
Package source: SC.MEB_1.0.tar.gz
Windows binaries: r-devel: SC.MEB_1.0.zip, r-devel-UCRT: SC.MEB_1.0.zip, r-release: SC.MEB_1.0.zip, r-oldrel: SC.MEB_1.0.zip
macOS binaries: r-release (arm64): not available, r-release (x86_64): not available, r-oldrel: not available

Linking:

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