R/getMOA.R

In bigomics/SPACEconnect: Stratified Perturbation Analysis by Correlation Enrichment of connectivity

#' Get the mechanism of action object
#'
#' @param dsea is a drug set enrichment object as an output of the function  getActiveDSEA()
#'
#' @return MoA Mechanism of Action object
#' @export
#' @importFrom fgsea  fgsea
#'
#' @examples # from the data-sets provided as examples within the package load the .rda files
#' # DrugsAnnot, mDrugEnrich, mFC
#' dsea <- getActiveDSEA(mDrugEnrich, DrugsAnnot, mFC, contr = colnames(mFC)[1])
#' Moa <- getMOA(dsea)
getMOA <- function(dsea) {
  ## meta-GSEA on MOA terms

  dt <- dsea$table

  moa.list <- lapply(
    as.character(dt$moa),
    function(s) trimws(strsplit(s, split = "[\\|;,]")[[1]])
  )

  names(moa.list) <- rownames(dt)
  moa <- setdiff(unlist(moa.list), c("", NA, " "))
  gmt <- lapply(moa, function(g) names(which(sapply(moa.list, function(t) (g %in% t)))))
  names(gmt) <- moa

  targets.list <- lapply(
    as.character(dt$target),
    function(s) trimws(strsplit(s, split = "[\\|;,]")[[1]])
  )
  names(targets.list) <- rownames(dt)
  targets <- setdiff(unique(unlist(targets.list)), c(NA, "", " "))
  gmtar <- lapply(targets, function(g) {
    names(which(sapply(targets.list, function(t) (g %in% t))))
  })
  names(gmtar) <- targets


  rnk <- dt$NES
  names(rnk) <- rownames(dt)

  # get drug class
  suppressWarnings(
    moa.class <- fgsea::fgsea(gmt, rnk, nperm = 20000)
  )
  moa.class <- moa.class[order(-abs(moa.class$NES)), ]

  # get gene targets
  suppressWarnings(
    moa.target <- fgsea::fgsea(gmtar, rnk, nperm = 20000)
  )
  moa.target <- moa.target[order(-abs(moa.target$NES)), ]

  moa <- list("drugClass" = moa.class, "geneTargets" = moa.target)



  return(moa)
}