R/plots_density_CV.R

In samWieczorek/DAPAR: Tools for the Differential Analysis of Proteins Abundance with R

#' Builds a densityplot of the CV of entities in the Biobase::exprs() table. 
#' of an object \code{MSnSet}. The variance is calculated for each 
#' condition present
#' in the dataset (see the slot \code{'Condition'} in the \code{Biobase::pData()} table).
#' 
#' @title Distribution of CV of entities
#' 
#' @param obj An object of class \code{MSnSet}
#' 
#' @param ... arguments for palette.
#' 
#' @return A density plot
#' 
#' @author Samuel Wieczorek
#' 
#' @examples
#' utils::data(Exp1_R25_pept, package='DAPARdata')
#' wrapper.CVDistD_HC(Exp1_R25_pept)
#' 
#' 
#' @export
#' 
wrapper.CVDistD_HC <- function(obj, ...){
  if (nrow(obj) == 0)
    return(NULL)
  
  qData <- Biobase::exprs(obj)
  conds <- Biobase::pData(obj)[,"Condition"]
  CVDistD_HC(qData, conds, ...)
}



#' Builds a densityplot of the CV of entities in the Biobase::exprs() table
#' of a object. The CV is calculated for each condition present
#' in the dataset (see the slot \code{'Condition'} in the \code{Biobase::pData()} table)
#' 
#' @title Distribution of CV of entities
#' 
#' @param qData A dataframe that contains quantitative data.
#' 
#' @param conds A vector of the conditions (one condition per sample).
#' 
#' @param pal xxx
#' 
#' @return A density plot
#' 
#' @author Samuel Wieczorek
#' 
#' @examples
#' utils::data(Exp1_R25_pept, package='DAPARdata')
#' conds <- Biobase::pData(Exp1_R25_pept)[,"Condition"]
#' CVDistD_HC(Biobase::exprs(Exp1_R25_pept), conds)
#' pal <- ExtendPalette(2, 'Dark2')
#' CVDistD_HC(Biobase::exprs(Exp1_R25_pept), conds, pal)
#' 
#' @import highcharter
#' @importFrom stats density var
#' 
#' @export
#' 
CVDistD_HC <- function(qData, 
                       conds=NULL, 
                       pal = NULL){
  
  if (is.null(conds)) {
    warning("The vector of conditions is empty. The plot cannot be drawn.")
    return(NULL)}
  
  conditions <- unique(conds)
  n <- length(conditions)
  
  
  if (is.null(pal)){
    pal <-  ExtendPalette(n)
  } else {
    if (length(pal) != n){
      warning("The color palette has not the same dimension as the number of samples. Set to default.")
      pal <- ExtendPalette(n)
    }
  }

  
  h1 <-  highchart() %>% 
    my_hc_chart(chartType = "spline", zoomType="x") %>%
    hc_colors(pal) %>%
    hc_legend(enabled = TRUE) %>%
    hc_xAxis(title = list(text = "CV(log(Intensity))")) %>%
    hc_yAxis(title = list(text = "Density")) %>%
    hc_tooltip(headerFormat= '',
               pointFormat = "<b>{series.name}</b>: {point.y} ",
               valueDecimals = 2) %>%
    my_hc_ExportMenu(filename = "logIntensity") %>%
    hc_plotOptions(
      series=list(
        connectNulls= TRUE,
        marker=list(
          enabled = FALSE)
      )
    )
  
  minX <- maxX <- 0
  maxY <- 0
  for (i in 1:n){
    if (length(which(conds == conditions[i])) > 1){
      t <- apply(qData[,which(conds == conditions[i])], 1, 
                 function(x) 100*var(x, na.rm=TRUE)/mean(x, na.rm=TRUE))
      tmp <- data.frame(x = density(t, na.rm = TRUE)$x,
                        y = density(t, na.rm = TRUE)$y)
      
      ymaxY <- max(maxY,tmp$y)
      xmaxY <- tmp$x[which(tmp$y==max(tmp$y))]
      minX <- min(minX, tmp$x)
      maxX <- max(maxX, 10*(xmaxY-minX))
      
      
      h1 <- h1 %>% hc_add_series(data=tmp, name=conditions[i]) }
  }
  
  h1 <- h1 %>%
    hc_chart(
      events = list(
        load = JS(paste0("function(){
                         var chart = this;
                         this.xAxis[0].setExtremes(",minX,",",maxX, ");
                         this.showResetZoom();}"))
      )
    )
  
  return(h1)
  
}