This vignette provides an introduction to the R package
DR.SC, where the function DR.SC implements the
model DR-SC, spatial clustering with hidden Markov random
field using empirical Bayes. The package can be installed with the
following command from Github:
install.packages('remotes')
remotes::install_github("feiyoung/DR.SC")
or install from CRAN
install.packages("DR.SC")
The package can be loaded with the command:
library("DR.SC")
#> Loading required package: parallel
#> Loading required package: spatstat.geom
#> Loading required package: spatstat.data
#> Loading required package: spatstat.univar
#> spatstat.univar 3.1-1
#> spatstat.geom 3.3-3
#> Warning: multiple methods tables found for 'union'
#> Warning: multiple methods tables found for 'intersect'
#> Warning: multiple methods tables found for 'setdiff'
#> Warning: multiple methods tables found for 'setequal'
#> DR.SC : 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. Check out our Package website (https://feiyoung.github.io/DR.SC/index.html) for a more complete description of the methods and analysesFor running big data, users can use the following system command to
set the C_stack unlimited in case of
R Error: C stack usage is too close to the limit.
ulimit -s unlimited