R/EulerrPlot.R

In afitz-gmu/DGE-Analysis: Bioinformatics plots for various Visualization

#' plot Prapotional venn diagram for upregulated and downregulated genes
#'
#' @param DE list of Differentially Expressed Genes from Various methods.
#' @param FoldChange is cuoff to mark genes as Differentially expressed
#' @param cutoff is either pvalue of FDR cutoff for filtering
#' @param type.sig vector \code{c('p', 'FDR')} default \code{'p'}
#' @importFrom gridExtra grid.arrange
#' @importFrom eulerr euler
#' @return \code{NULL}
#'
#' @examples
#'
#' data("DEG")
#' DE.list<-list("edger" =dge_edger, "edgerql" = dge_edgerql,
#' "deseq2" = dge_deseq2, "voom" = dge_voom )
#' EulerrPlot(DE=DE.list , FoldChange=1.5 , cutoff =0.01 , type.sig ="FDR")
#'
#'
#' @export

EulerrPlot <- function(DE, FoldChange = 0, cutoff=0.05 , type.sig='p')
{
  stopifnot(is.list(DE), is.numeric(FoldChange) , is.numeric(cutoff))
  
  FC <- c("log2FoldChange", "logFC")
  pv <-c( "pvalue", "P.Value", "PValue")
  if (type.sig=="FDR"){
     pv <-c( "FDR", "padj", "adj.P.Val")
  }
  names<-names(DE)
  up<-list()
  down<-list()
  for(name in names)
  {

    DERes<-DE[[name]]
    DERes$regulation<-"No"
    DERes$regulation[DERes[intersect(FC , colnames(DERes))] > FoldChange &
                       DERes[intersect(pv , colnames(DERes))] < cutoff] <- "UP"
    up[[name]]<-row.names(DERes[DERes$regulation == "UP",])
    DERes$regulation[DERes[intersect(FC , colnames(DERes))] < -1* FoldChange
                  & DERes[intersect(pv , colnames(DERes))] < cutoff] <- "DOWN"
    down[[name]]<-row.names(DERes[DERes$regulation == "DOWN",])

  }
  gridExtra::grid.arrange( graphics::plot(euler(up) , quantites=TRUE ,
                          main="UpRegulated Genes") ,graphics::plot(euler(down),
                          quantites=TRUE , main="DownRegulated Genes"), nrow=1)
}