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This vignette provides an introduction to the R package
PRECAST, where the function PRECAST implements
the model PRECAST, a PRobabilistic Embedding and Clustering
with alignment for Spatial Transcriptomics data integration . The
package can be installed with the following command from Github:
install.packages('remotes')
remotes::install_github("feiyoung/PRECAST")
or install from CRAN
install.packages("PRECAST")
The package can be loaded with the command:
library("PRECAST")
#> Loading required package: parallel
#> Loading required package: gtools
#> PRECAST : 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>. Check out our Package website (https://feiyoung.github.io/PRECAST/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 unlimitedThese 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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