An R interface of Python module scsampler. It is designed for fast diversity-preserving subsampling of large-scale single-cell transcriptomic data.
The package relies on the R package reticulate for calling scsampler in Python (which is designed for scanpy).
Please first install scsampler and scanpy from PyPI:
pip install scanpy
pip install scsampler
Then install rscsampler in R:
install.packages("devtools")
install.packages("reticulate")
library(devtools)
devtools::install_github("SONGDONGYUAN1994/rscsampler")
The package can take the input dataset in the format of: SingleCellExperiment, SeuratObject or a matrix. By default, we use the top 50 PCs for cell selection. Here
we show an example of the top PCs examplary dataset:
library(reticulate)
library(rscsampler)
data("pbmc68k")
subsample_index <- scsampler(dat = pbmc68k, use_pca = FALSE, run_pca = FALSE, fraction = 0.1) ## 10% subsamples
We still recommend users using the Python module scsampler since R is not very ideal for dealing with large datasets.
Any questions or suggestions on rscsampler are welcomed! If you have any questions, please report it on issues or contact Dongyuan (dongyuansong@ucla.edu).