R/DensityView.R

In MAGeCKFlute: Integrative Analysis Pipeline for Pooled CRISPR Functional Genetic Screens

#' Density plot for gene beta scores in Control and Treatment
#'
#' Plot the density of gene beta scores in two samples.
#'
#' @docType methods
#' @name DensityView
#' @rdname DensityView
#'
#' @param beta Data frame, including \code{samples} as columns.
#' @param samples Character, specifying sample names in \code{beta}.
#' @param main As in 'plot'.
#' @param xlab As in 'plot'.
#' @param filename Figure file name to create on disk. Default filename="NULL", which means
#' don't save the figure on disk.
#' @param width As in ggsave.
#' @param height As in ggsave.
#' @param ... Other available parameters in ggsave.
#'
#' @return An object created by \code{ggplot}, which can be assigned and further customized.
#'
#' @author Wubing Zhang
#'
#' @seealso \code{\link{ViolinView}}
#'
#' @examples
#' file3 = file.path(system.file("extdata", package = "MAGeCKFlute"),
#' "testdata/mle.gene_summary.txt")
#' dd = ReadBeta(file3)
#' DensityView(dd, samples=c("dmso", "plx"))
#' #or
#' DensityView(dd[, c("dmso", "plx")])
#'
#' @importFrom reshape2 melt
#'
#' @export

#===Distribution of beta scores======================================
DensityView <- function(beta, samples = NULL, main = NULL,xlab = "Beta Score",
                        filename = NULL, width = 5, height = 4, ...){
  if(!is.null(samples) && length(samples)>0){ beta = beta[, samples, drop = FALSE]}
  dd1 = reshape2::melt(beta,id=NULL)
  if(!"variable" %in% colnames(dd1)){
    dd1$variable = colnames(beta)
  }
  #==========
  p=ggplot(data=dd1, aes_string(x="value",color="variable",group="variable"))
  p=p+geom_density()
  # p=p+facet_wrap(~variable,nrow=1)
  # p=p+ggsci::scale_color_npg()
  p=p+labs(color=NULL)
  p=p+theme(legend.justification = c(1, 1), legend.position = c(0.99, 0.99))
  # p=p+theme(legend.text = element_text(size=8))
  p=p+labs(x=xlab, y="Density", title=main)
  p = p + theme(text = element_text(colour="black",size = 14, family = "Helvetica"),
                plot.title = element_text(hjust = 0.5, size=18),
                axis.text = element_text(colour="gray10"))
  p = p + theme(axis.line = element_line(size=0.5, colour = "black"),
                panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
                panel.border = element_blank(), panel.background = element_blank(),
                legend.key = element_rect(fill = "transparent"))

  if(!is.null(filename)){
    ggsave(plot=p, filename=filename, units = "in", width=width, height=height, ...)
  }
  return(p)
}



#' Density plot
#'
#' Plot the density of beta score deviations.
#'
#' @docType methods
#' @name DensityDiffView
#'
#' @param beta Data frame, including \code{ctrlname} and \code{treatname} as columns.
#' @param ctrlname A character, specifying the name of control sample.
#' @param treatname A character, specifying the name of treatment sample.
#' @param main As in 'plot'.
#' @param filename Figure file name to create on disk. Default filename="NULL", which means no output.
#' @param width As in ggsave.
#' @param height As in ggsave.
#' @param ... Other parameters in ggsave.
#'
#' @return An object created by \code{ggplot}, which can be assigned and further customized.
#'
#' @author Wubing Zhang
#'
#'
#' @examples
#' file3 = file.path(system.file("extdata", package = "MAGeCKFlute"),
#' "testdata/mle.gene_summary.txt")
#' dd = ReadBeta(file3)
#' # Density plot of beta score deviation between control and treatment
#' DensityDiffView(dd, ctrlname = "dmso", treatname = "plx")
#'
#'
#' @export

#===Distribution of beta scores======================================

DensityDiffView <- function(beta, ctrlname="Control", treatname="Treatment", main=NULL,
                            filename=NULL, width = 5, height = 4, ...){
  d = beta
  d$Diff = rowMeans(d[,treatname,drop=FALSE])-rowMeans(d[,ctrlname,drop=FALSE])
  d$r = rnorm(length(d$Diff), mean=0, sd=sd(d$Diff)-0.01)
  p = ggplot(d, aes_string("Diff"))
  p = p + geom_density(colour="black")
  # p = p + geom_histogram(aes(y = ..density..), fill="gray90", binwidth=0.02)
  p = p + geom_density(aes_string("r"), linetype="dashed", colour="red")
  p = p + geom_vline(xintercept = 0,linetype="dashed")
  p = p + theme(text = element_text(colour="black",size = 14, family = "Helvetica"),
                plot.title = element_text(hjust = 0.5, size=18),
                axis.text = element_text(colour="gray10"))
  p = p + theme(axis.line = element_line(size=0.5, colour = "black"),
                panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
                panel.border = element_blank(), panel.background = element_blank(),
                legend.key = element_rect(fill = "transparent"))
  p = p + labs(x="Treat-Control Beta Score", y="Density", title=main)

  if(!is.null(filename)){
    ggsave(plot=p, filename=filename, units = "in", width=width, height=height, ...)
  }
  return(p)
}