R/markerExpression.R

In kordastilab/ImmunoCluster: Fast and accesible Immune profiling CyTOF data

#' @rdname markerExpression
#'
#' @title Generate an dotplot of a dimensionality reduction with marker expression overlaid as a heat dimension.
#'
#' @param indata a \code{\link[SingleCellExperiment]{SingleCellExperiment}}.
#' @param assay the SCE assay to choose from.
#' @param reducedDim a sting representing the dimensionality reduction stored in the SCE to plot
#' @param markers a sting or vecotor of stings representing the markers to select for plotting
#' @param ncol a numeric representing the number of colums to arrange the plots into
#' @param nrow a numeric representing the number of rows to arrange the plots into
#' @param col a vector of two strings representing the colour gradient to be used as the heat component on the expression plot
#' @param colMidpoint a numeric representing the midpoint of the colour gradient specified in `col`, the default is 0
#' @param pointSize a numeric specifying the point size of the dots on the plot, default is 0.5
#' @param plotting_options The rest of the options can all found in the ggplot2 documentation. These options control various elements of the ggplot2 output.
#'
#' @author Kevin Blighe, James Opzoomer \email{james.opzoomer@kcl.ac.uk}
#'
#' @return a \code{SingleCellExperiment} object.
#'
#' @examples
#' # Download complete ImmunoCluster SCE object from zenodo
#' sce_gvhd = readRDS(url("https://zenodo.org/record/3801882/files/sce_gvhd.rds"))
#'
#' # Run UMAP and store in sce object
#' sce_gvhd = performUMAP(sce_gvhd)
#'
#' expression_markers =  c('CD3', 'CD4', 'CD8a', 'CD11b', 'CD19', 'CD56')
#'
#' exp_plot_umap = markerExpression(sce_gvhd,
#'                                 markers = expression_markers,
#'                                 reducedDim = 'UMAP',
#'                                 title = 'UMAP',
#'                                 nrow = 1, ncol = 6,
#'                                 pointSize = 0.05,
#'                                 legendKeyHeight = 1.0,
#'                                 legendLabSize = 14,
#'                                 stripLabSize = 20,
#'                                 axisLabSize = 18,
#'                                 titleLabSize = 20,
#'                                 captionLabSize = 22)
#'
#' @import reshape2
#'
#' @export
#'
markerExpression <- function(
  indata,
  layout = NULL,
  assay = 'scaled',
  reducedDim = 'UMAP',
  dimColnames = colnames(as.data.frame(reducedDim(indata, reducedDim))),
  markers = sample(rownames(indata), 6),
  ncol = 3,
  nrow = 2,
  col = c('darkblue', 'yellow'),
  colMidpoint = 0,
  alpha = c(0.0, 1),
  pointSize = 0.5,
  legendPosition = 'right',
  legendLabSize = 12,
  legendIconSize = 5.0,
  legendKeyHeight = 2.5,
  xlim = NULL,
  ylim = NULL,
  celllab = NULL,
  labSize = 3.0,
  labhjust = 1.5,
  labvjust = 0,
  drawConnectors = TRUE,
  widthConnectors = 0.5,
  colConnectors = 'black',
  xlab = dimColnames[1],
  xlabAngle = 0,
  xlabhjust = 0.5,
  xlabvjust = 0.5,
  ylab = dimColnames[2],
  ylabAngle = 0,
  ylabhjust = 0.5,
  ylabvjust = 0.5,
  axisLabSize = 16,
  stripLabSize = 16,
  title = 'Individual marker expression',
  subtitle = '',
  caption = ifelse(is(indata, 'SingleCellExperiment'),
    paste0('Total cells, ',
      nrow(as.data.frame(reducedDim(indata, reducedDim))[!is.na(reducedDim(indata, reducedDim)[,1]),])),
    paste0('Total cells, ', nrow(layout))),
  titleLabSize = 16,
  subtitleLabSize = 12,
  captionLabSize = 12,
  hline = NULL,
  hlineType = 'longdash',
  hlineCol = 'black',
  hlineWidth = 0.4,
  vline = NULL,
  vlineType = 'longdash',
  vlineCol = 'black',
  vlineWidth = 0.4,
  gridlines.major = FALSE,
  gridlines.minor = FALSE,
  borderWidth = 0.8,
  borderColour = 'black')
{
  dim1 <- dim2 <- Expression <- lab <- NULL

  # create a base theme that will later be modified
  th <- theme_bw(base_size=24) +

    theme(
      legend.background = element_rect(),

      title = element_text(size = legendLabSize),

      plot.title=element_text(angle=0, size=titleLabSize,
        face='bold', vjust=1),
      plot.subtitle=element_text(angle = 0, size = subtitleLabSize,
        face = 'plain', vjust = 1),
      plot.caption=element_text(angle = 0, size = captionLabSize,
        face = 'plain', vjust = 1),

      axis.text.x=element_text(angle = xlabAngle, size = axisLabSize,
        hjust = xlabhjust, vjust = xlabvjust),
      axis.text.y=element_text(angle = ylabAngle, size = axisLabSize,
        hjust = ylabhjust, vjust = ylabvjust),
      axis.title = element_text(size = axisLabSize),

      legend.title  =element_blank(),
      legend.position = legendPosition,
      legend.key = element_blank(),
      legend.key.size = unit(0.5, 'cm'),
      legend.text = element_text(size = legendLabSize),
      legend.key.height = unit(legendKeyHeight, 'cm'),

      strip.text.x = element_text(size = stripLabSize,
        face = 'bold', margin = margin(b = 5, t = 5)))

  if (is(indata, 'SingleCellExperiment')) {

    message('--input data class is SingleCellExperiment')
    plotobj <- as.data.frame(reducedDim(indata, reducedDim)[,dimColnames])
    plotobj <- data.frame(plotobj,
      as.data.frame(t(as.matrix(assay(indata, assay)))))
    plotobj <- melt(plotobj, id.vars = dimColnames)

  } else {

    message('--input data class is ', class(indata))

    if (is.null(layout)) {
      stop('When the input data is a non-SingleCellExperiment object, ',
        '\'indata\' must relate to an expression matrix (cells as columns; ',
        'genes as rows), while \'layout\' must be non-NULL and relate to ',
        'a 2-dimensional embedding containing columns specified by ',
        '\'dimColnames\'')
    } else if (!all(rownames(layout) == colnames(indata))) {
      stop('\'rownames(layout)\' must be equal to \'colnames(indata)\'')
    }

    plotobj <- as.data.frame(layout[,dimColnames])
    plotobj <- data.frame(plotobj, as.data.frame(t(as.matrix(indata))))
    plotobj <- melt(plotobj, id.vars = dimColnames)
  }
  colnames(plotobj) <- c('dim1','dim2','Marker','Expression')

  plotobj <- plotobj[which(plotobj$Marker %in% markers),]

  # set plot labels (e.g. cell names)
  if (!is.null(celllab)) {
    plotobj$lab <- rep(colnames(indata), length(markers))
    plotobj <- as.data.frame(plotobj, stringsAsFactors = FALSE)

    names.new <- rep(NA, length(plotobj$lab))
    indices <- which(plotobj$lab %in% celllab)
    names.new[indices] <- plotobj$lab[indices]
    plotobj$lab <- names.new
  }

  if (is.null(xlim)) {
    xlim <- c(
      min(plotobj[,'dim1'], na.rm = TRUE) - 1,
      max(plotobj[,'dim1'], na.rm = TRUE) + 1)
  }

  if (is.null(ylim)) {
    ylim <- c(
      min(plotobj[,'dim2'], na.rm = TRUE) - 1,
      max(plotobj[,'dim2'], na.rm = TRUE) + 1)
  }

  # order by expression level to ensure that highly expressed are coloured last
  plotobj <- plotobj[order(plotobj$Expression, decreasing = FALSE),]

  # Remove dimReduc downsample NAs
  plotobj = plotobj[!is.na(plotobj$dim1),]

  # initialise the plot object
  plot <- ggplot(plotobj, aes(x = dim1, y = dim2, alpha = Expression)) + th +

    guides(
      fill = guide_legend(),
      shape = guide_legend(),
      alpha = FALSE)

  plot <- plot + geom_point(aes(colour = Expression), size = pointSize)

  if (length(col) == 2) {
    plot <- plot +
       scale_colour_gradient(
         low = col[1],
         high = col[2],
         name = 'Expression')
  } else if (length(col) == 3) {
    plot <- plot +
      scale_colour_gradient2(
        low = col[1],
        mid = col[2],
        high = col[3],
        midpoint = colMidpoint,
        limits = c(min(plotobj$Expression), max(plotobj$Expression)),
        space = 'Lab',
        name = 'Expression')
  }

  plot <- plot + #scale_alpha(range = c(alpha[1], alpha[2]), guide = FALSE) +
    facet_wrap( ~ Marker, nrow = nrow, ncol = ncol)

  # add elements to the plot for xy labeling and axis limits
  plot <- plot + xlab(xlab) + ylab(ylab)
  if (!is.null(xlim)) {
    plot <- plot + xlim(xlim[1], xlim[2])
  }
  if (!is.null(ylim)) {
    plot <- plot + ylim(ylim[1], ylim[2])
  }

  # add elements to the plot for title, subtitle, caption
  plot <- plot + labs(title = title,
    subtitle = subtitle, caption = caption)

  # add elements to the plot for vlines and hlines
  if (!is.null(vline)) {
    plot <- plot + geom_vline(xintercept = vline,
      linetype = vlineType,
      colour = vlineCol,
      size = vlineWidth)
  }
  if (!is.null(hline)) {
    plot <- plot + geom_hline(yintercept = hline,
      linetype = hlineType,
      colour = hlineCol,
      size = hlineWidth)
  }

  # border around plot
  plot <- plot +
    theme(panel.border = element_rect(
      colour = borderColour,
      fill = NA,
      size = borderWidth))

  # gridlines
  if (gridlines.major == TRUE) {
    plot <- plot + theme(panel.grid.major = element_line())
  } else {
    plot <- plot + theme(panel.grid.major = element_blank())
  }
  if (gridlines.minor == TRUE) {
    plot <- plot + theme(panel.grid.minor = element_line())
  } else {
    plot <- plot + theme(panel.grid.minor = element_blank())
  }

  if (!is.null(celllab)) {
    if (drawConnectors == TRUE && is.null(celllab)) {
      plot <- plot + geom_text_repel(
        data = plotobj,
          aes(label = lab),
          size = labSize,
          segment.color = colConnectors,
          segment.size = widthConnectors,
          hjust = labhjust,
          vjust = labvjust)
    } else if (drawConnectors == TRUE && !is.null(celllab)) {
      plot <- plot + geom_text_repel(
        data=subset(plotobj,
          !is.na(plotobj[,'lab'])),
          aes(label = lab),
          size = labSize,
          segment.color = colConnectors,
          segment.size = widthConnectors,
          hjust = labhjust,
          vjust = labvjust)
    } else if (drawConnectors == FALSE && !is.null(celllab)) {
      plot <- plot + geom_text(
        data=subset(plotobj,
          !is.na(plotobj[,'lab'])),
          aes(label = lab),
          size = labSize,
          check_overlap = TRUE,
          hjust = labhjust,
          vjust = labvjust)
    } else if (drawConnectors == FALSE && is.null(celllab)) {
      plot <- plot + geom_text(
        data = plotobj,
          aes(label = lab),
          size = labSize,
          check_overlap = TRUE,
          hjust = labhjust,
          vjust = labvjust)
    }
  }

  return(plot)
}