R/Visualization.R

In RyDe4/ChIPanalyzer: ChIPAnalyzer

#'Plot the abundance of Predicted G-quadruplexes
#'Relative to a Central Postiion
#'
#'Using a vector returned by getQuadCoveragePercentage(),
#'plot the percentage of peaks that have G-quadruplexes across
#'positions in sequences around the ChIP-SEQ peaks
#'
#'@param featurePercentages a numeric vector containing percentages such as
#' a vector returned by getQuadCoveragePercentage()
#'
#'@param title a string specifying the title of the plot
#'
#'@return returns a plot of G-Quadruplex Abundance
#'
#'@examples
#' path <- system.file("extdata", "MAZ_very_small_test.bed", package = "ChIPAnalyzer")
#' reports <- findQuads(bedPath = path,
#'  seqWidth = 200,
#'   assemblyVersion = "hg19")
#' qMatrix <- getQuadMatrix(quadReports = reports)
#' quadCoveragePercentage <- getQuadCoveragePercentage(quadMatrix = qMatrix)
#' plotQuadPosition(quadCoveragePercentage, "MAZ G-Quad Abundance")
#'
#'@export
plotQuadPosition <- function (featurePercentages, title) {
  if (length(featurePercentages) < 1) {
    stop("empty vector provided")
  }
  #calculate the bounds for the x axis
  leftBound <- as.integer(-1*floor(length(featurePercentages)/2))
  rightBound <- as.integer(ceiling(length(featurePercentages)/2) - 1)
  #display the plot
  plot(c(leftBound, rightBound),
       c(0, 100),
       type = "n",
       xlab = "Position",
       ylab = "Percentage")
  lines(x = leftBound:rightBound,
        type = "l",
        y = featurePercentages,
        col = "blue")
  abline(v = 0)
  title(title)

  quadPlot <- recordPlot()

  return(quadPlot)
}

#'Generate a Pie Chart of The percentage of ChIP peak nucleotides that
#'are methylated
#'
#'Using the dataframe of methylation data for ChIP peak nucleotides
#' generated by getMethylOverlap, create a pie chart showing the
#' percentage of peak sites that are methylated
#'
#'@param methylOverlapData a data frame with a coverage column specifying
#' the percentage of reads methylated. This column must be named coverage
#'
#'@return returns a pie plot of methylation percentages
#'
#'@examples
#' path1 <- system.file("extdata", "MAZ_high_score.bed", package = "ChIPAnalyzer")
#' path2 <- system.file("extdata", "HcfUMethylData.bed", package = "ChIPAnalyzer")
#' overlap <- getMethylOverlap(path1, path2)
#' plotMethylPercentage(overlap)
#'
#'@export
plotMethylPercentage <- function(methylOverlapData) {
  if(nrow(methylOverlapData) < 1) {
    stop("empty dataframe provided")
  }
  #calculate the average percentages of reads methylated at each position
  avgPercentMethyl <- mean(methylOverlapData$coverage)
  #define the labels and sections for the pie chart
  pieLabels <-c(paste(round(avgPercentMethyl, 4), "%"),
                paste(round(100 - avgPercentMethyl, 4), "%"))
  sections <- c(avgPercentMethyl, 100 - avgPercentMethyl)
  #display the plot
  pie(sections, pieLabels,
      col = c("green", "blue"),
      cex = 0.7)
  title("Avg % Reads Methylated", cex = 0.3)
  legend("topright", c("Methylated", "Not Methylated"),
         cex = 0.5, fill= c("green", "blue"))
  methylPiePlot <- recordPlot()

  return(methylPiePlot)
}