R/drimpute.R
In reggenlab/UniPath: UniPath provides robust statistical methods to represent every single cell using pathway and gene-set enrichment scores. It can be used with both single cell RNA-seq and single cell ATAC-seq profile with scalability for atlas scale data-sets. Unipath comes with several features like psuedo-temporal ordering using pathway scores and unconventional way of enumerating differences between two cell populations.
Defines functions
drimpute
Documented in
drimpute
#' Imputation of scATAC-seq profiles
#'
#' @param countFile scATAC-seq count matrix
#'
#' @return imputed count matrix
#' @export
#'
#' @examples
#' drimpute()
drimpute = function(countFile){
X = read.table(countFile,sep=",",header=T,stringsAsFactors = F,row.names = 1)
X = as.matrix(X)
X.log <- log(X + 1)
X.log = X.log[,apply(X.log, 2, var, na.rm=TRUE) != 0]
X.imp <- DrImpute::DrImpute(X.log)
return(X.imp)
}
reggenlab/UniPath documentation built on Nov. 26, 2020, 8:09 a.m.
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Defines functions drimpute
Documented in drimpute
#' Imputation of scATAC-seq profiles
#'
#' @param countFile scATAC-seq count matrix
#'
#' @return imputed count matrix
#' @export
#'
#' @examples
#' drimpute()
drimpute = function(countFile){
X = read.table(countFile,sep=",",header=T,stringsAsFactors = F,row.names = 1)
X = as.matrix(X)
X.log <- log(X + 1)
X.log = X.log[,apply(X.log, 2, var, na.rm=TRUE) != 0]
X.imp <- DrImpute::DrImpute(X.log)
return(X.imp)
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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