R/solveOLS.R

In sistia01/DWLS: Gene Expression Deconvolution Using Dampened Weighted Least Squares

#' @title solveOLS
#'
#' @description This function solves or the unknown parameters
#' using ordinary least squares (OLS). It is constrained such
#' that cell type numbers are greater than 0.
#'
#' @param S List output from trimData$sig (S)
#' @param B List output from trimData$bulk (B)
#'
#' @return Cell-type proportion
#'
#' @examples
#' \donttest{
#' #Sig
#' #url <- "https://github.com/sistia01/DWLS/raw/main/inst/extdata/Sig.RData"
#' #dest <- "data/Sig.RData"
#' #download.file(url, dest)
#' #load("data/Sig.RData")
#' load(system.file("extdata", "Sig.RData", package = "DWLS"))
#'
#' #dataBulk
#' #url <- "https://github.com/sistia01/DWLS/raw/main/inst/extdata/dataBulk.RData"
#' #dest <- "data/dataBulk.RData"
#' #download.file(url, dest)
#' #load("data/dataBulk.RData")
#' load(system.file("extdata", "dataBulk.RData", package = "DWLS"))
#'
#' trimmed <- trimData(Sig, dataBulk)
#' S <- trimmed$sig
#' B <- trimmed$bulk
#' solveOLS(S, B)
#'}
#' @export solveOLS
#'
#' @importFrom dplyr "%>%"

solveOLS<-function(S,B){
  D<-t(S)%*%S
  d<-t(S)%*%B
  A<-cbind(diag(dim(S)[2]))
  bzero<-c(rep(0,dim(S)[2]))
  solution<-solve.QP(D,d,A,bzero)$solution
  names(solution)<-colnames(S)
  print(round(solution/sum(solution),5))
  return(solution/sum(solution))
}