knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "README-" )
2019/08/20:
2018/08/15:
scImpute
is developed to accurately and robustly impute the dropout values in scRNA-seq data. scImpute
can be applied to raw read count matrix before the users perform downstream analyses such as
The users can refer to our paper An accurate and robust imputation method scImpute for single-cell RNA-seq data for a detailed description of the modeling and applications.
Any suggestions on the package are welcome! For technical problems, please report to Issues. For suggestions and comments on the method, please contact Wei (liw@ucla.edu) or Dr. Jessica Li (jli@stat.ucla.edu).
The package is not on CRAN yet. For installation please use the following codes in R
install.packages("devtools") library(devtools) install_github("Vivianstats/scImpute")
scImpute
can be easily incorporated into existing pipeline of scRNA-seq analysis.
Its only input is the raw count matrix with rows representing genes and columns representing cells. It will output an imputed count matrix with the same dimension.
In the simplest case, the imputation task can be done with one single function scimpute
:
scimpute(# full path to raw count matrix count_path = system.file("extdata", "raw_count.csv", package = "scImpute"), infile = "csv", # format of input file outfile = "csv", # format of output file out_dir = "./", # full path to output directory labeled = FALSE, # cell type labels not available drop_thre = 0.5, # threshold set on dropout probability Kcluster = 2, # 2 cell subpopulations ncores = 10) # number of cores used in parallel computation
This function returns the column indices of outlier cells, and creates a new file scimpute_count.csv
in out_dir
to store the imputed count matrix. Please note that we recommend applying scImpute on the whole-genome count matrix. A filtering step on genes is acceptable but most genes should be present to ensure robust identification of dropouts.
For detailed usage, please refer to the package manual or vignette.
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