add R scripts for clone density plot and histogram

NAMESPACE

@@ -24,6 +24,7 @@ export(create.ccf.heatmap)
 export(create.cluster.heatmap)
 export(create.ccf.summary.heatmap)
 export(create.clone.genome.distribution.plot)
+export(create.ccf.densityplot)
 
 export(data.frame.to.array)
 export(update.descendant.property)

NEWS.md

@@ -12,7 +12,8 @@
 * Add option to use scale bars instead of y-axes.
 * Wrapper function for `SRCgrob` to automatically save plots to file
 * Add option to annotate the CCF summary heatmap with the cell values.
-
+* Function to generate single-sample density plot
+
 ## Update
 * Fixed angle calculation bug where child angles do not follow
   their parent angle, instead moving "downward" at 0 degrees.

R/calculate.density.R

@@ -0,0 +1,19 @@
+calculate.density <- function(
+    x,
+    value = 'genome.pos',
+    group = 'clone.id',
+    scale = TRUE,
+    ...
+    ) {
+
+    if (nrow(x) <= 1) {
+        return(NULL);
+        }
+    density <- density(x = x[[value]], bw = 'nrd', na.rm = TRUE, ...);
+    density.df <- as.data.frame(density[c('x', 'y')]);
+    density.df$clone.id <- unique(x[[group]]);
+    if (scale) {
+        density.df$y <- nrow(x) / sum(density.df$y) * density.df$y;
+        }
+    return(density.df)
+    }

R/create.ccf.densityplot.R

@@ -0,0 +1,115 @@
+create.ccf.densityplot <- function(
+    x,
+    filename = NULL,
+    clone.colours = NULL,
+    breaks = 100,
+    xlab.label = 'CCF',
+    ylab.label = 'SNV Density',
+    xlimits = c(0, 1.5),
+    xat = seq(0, 1.5, 0.25),
+    legend.size = 3,
+    legend.title.cex = 1.2,
+    legend.label.cex = 1,
+    legend.x = 0.8,
+    legend.y = 0.9,
+    height = 6,
+    width = 10,
+    size.units = 'in',
+    resolution = 1000,
+    ...
+    ) {
+
+    if (is.null(clone.colours)) {
+        clone.colours <- get.colours(x$clone.id, return.names = TRUE);
+        }
+
+    # calculate mean CCF and nsnv per cluster -----------------------------------------------------
+    mean.ccf <- aggregate(CCF ~ clone.id, data = x, FUN = mean);
+    nsnv <- aggregate(SNV.id ~ clone.id, data = x, FUN = length);
+
+    # calculate densities for each cluster --------------------------------------------------------
+    density.list <- list();
+    for (k in unique(x$clone.id)) {
+        density.list[[k]] <- calculate.density(
+            x = x[x$clone.id == k, ],
+            value = 'CCF',
+            adjust = 1,
+            scale = FALSE
+            );
+        }
+    density.df <- do.call(rbind, density.list);
+    density.df$y <- density.df$y * (nsnv$SNV.id[match(density.df$clone.id, nsnv$clone.id)] / nrow(x));
+
+
+    # get plot legend -----------------------------------------------------------------------------
+    legend.label <- sapply(names(clone.colours), function(k) {
+        nsnv <- nsnv[nsnv$clone.id == k, ]$SNV.id;
+        return(paste0(k, ' (', nsnv, ')'));
+        });
+    clone.legend <- BoutrosLab.plotting.general::legend.grob(
+        list(
+            legend = list(
+                title = 'Clone (SNVs)',
+                labels = legend.label[names(clone.colours)],
+                colours = c(clone.colours),
+                border = 'black'
+                )
+            ),
+        size = legend.size,
+        title.just = 'left',
+        title.cex = legend.title.cex,
+        label.cex = legend.label.cex
+        );
+
+    ymax <- ceiling(max(density.df$y, na.rm = TRUE));
+
+    hist <- BoutrosLab.plotting.general::create.histogram(
+        x = x$CCF,
+        type = 'density',
+        col = 'gray90',
+        border.col = 'gray30',
+        lwd = 0.1,
+        xlab.label = xlab.label,
+        ylab.label = ylab.label,
+        xlimits = xlimits,
+        xat = xat,
+        ylimits = c(-0.05, 1.05) * ymax,
+        legend = list(inside = list(
+            fun = clone.legend,
+            x = legend.x,
+            y = legend.y
+            )),
+        ...
+        );
+
+    scatter <- BoutrosLab.plotting.general::create.scatterplot(
+        formula = y ~ x,
+        data = density.df,
+        groups = density.df$clone.id,
+        type = 'l',
+        lwd = 3,
+        col = clone.colours,
+        xlimits = xlimits,
+        ylimits = c(-0.05, 1.05) * ymax,
+        abline.v = mean.ccf$CCF,
+        abline.lwd = 0.5,
+        abline.lty = 'longdash',
+        abline.col = 'gray50',
+        add.text = TRUE,
+        text.labels = lapply(mean.ccf$CCF, round, 2),
+        text.x = mean.ccf$CCF,
+        text.y = ymax,
+        text.fontface = 'bold',
+        text.cex = legend.title.cex
+        );
+
+    combn.plt <- hist + scatter;
+    return(BoutrosLab.plotting.general::write.plot(
+        trellis.object = combn.plt,
+        filename = filename,
+        height = height,
+        width = width,
+        size.units = size.units,
+        resolution = resolution
+        ));
+    }

R/create.clone.genome.distribution.densityplot.R

@@ -8,7 +8,7 @@ create.clone.genome.distribution.densityplot <- function(
 
     return(BoutrosLab.plotting.general::create.scatterplot(
         filename = save.plt,
-        formula = count ~ x,
+        formula = y ~ x,
         data = density.df,
         groups = density.df$clone.id,
         xlab.label = 'Chromosome',
@@ -24,17 +24,3 @@ create.clone.genome.distribution.densityplot <- function(
         ...
         ));
     }
-
-calculate.density.and.scale <- function(cluster.df) {
-    # density should be generated using unque SNV count
-    density <- density(
-        x = cluster.df$genome.pos,
-        bw = 'nrd',
-        adjust = 0.05, # set to 1E9/3E9 to get density per megabase
-        na.rm = TRUE);
-    density.df <- as.data.frame(density[c('x','y')]);
-    density.df$clone.id <- unique(cluster.df$clone.id);
-    density.df$count <- nrow(cluster.df) / sum(density.df$y) * density.df$y;
-
-    return(density.df)
-    }

R/create.clone.genome.distribution.plot.R

@@ -104,8 +104,9 @@ create.clone.genome.distribution.plot.per.sample <- function(
             warning(paste('Skipping clone', k, 'in sample', unique(sample.df$ID), 'since there is only one SNV'));
             next;
         }
-        density.list[[k]] <- calculate.density.and.scale(
-            cluster.df = sample.df[sample.df$clone.id == k, ]
+        density.list[[k]] <- calculate.density(
+            x = sample.df[sample.df$clone.id == k, ],
+            adjust = 0.05
             );
         }
     density.df <- do.call(rbind, density.list);

R/create.cluster.heatmap.R

@@ -15,6 +15,7 @@ create.cluster.heatmap <- function(
     xaxis.fontface = 'bold',
     y.spacing = 1,
     colour.scheme = c('white', 'blue'),
+    plot.objects.heights = c(1, 0.2),
     ...
     ) {
 
@@ -94,7 +95,7 @@ create.cluster.heatmap <- function(
         plot.objects = list(hm, cov),
         layout.width = 1,
         layout.height = 2,
-        plot.objects.heights = c(1, 0.2),
+        plot.objects.heights = plot.objects.heights,
         legend = list(right = list(
             fun = legend.clone
         )),

R/create.phylogenetic.tree.R

@@ -12,10 +12,10 @@ create.phylogenetic.tree <- function(
     tree <- as.data.frame(tree);
     if ('node.id' %in% colnames(tree)) {
         rownames(tree) <- tree$node.id;
-         if (!'label' %in% colnames(tree)) {
+        if (!'label' %in% colnames(tree)) {
             tree$label <- tree$node.id;
             }
-       }
+        }
 
     plt <- SRCGrob(
         tree,

man/create.ccf.densityplot.Rd

@@ -0,0 +1,51 @@
+\name{create.ccf.densityplot}
+\alias{create.ccf.densityplot}
+\title{CCF Density Plot}
+\description{
+Creates a density plot of cancer cell fraction (CCF) distribution across a sample.
+}
+\usage{
+create.ccf.densityplot(
+    x,
+    filename = NULL,
+    clone.colours = NULL,
+    breaks = 100,
+    xlab.label = 'CCF',
+    ylab.label = 'SNV Density',
+    xlimits = c(0, 1.5),
+    xat = seq(0, 1.5, 0.25),
+    legend.size = 3,
+    legend.title.cex = 1.2,
+    legend.label.cex = 1,
+    legend.x = 0.8,
+    legend.y = 0.9,
+    height = 6,
+    width = 10,
+    size.units = 'in',
+    resolution = 1000,
+    ...
+    );
+}
+\arguments{
+    \item{x}{A data-frame with the following column names: 'SNV.id', 'clone.id', 'CCF'.}
+    \item{filename}{Filename for tiff output, or if NULL returns the trellis object itself. Defaults to \code{NULL}.}
+    \item{clone.colours}{Named list to provide a colour scheme for the clone ID covariate bar. If NULL, colours will be randomly generated. Defaults to \code{NULL}.}
+    \item{breaks}{Number of breaks for the histogram. Defaults to 100.}
+    \item{xlab.label}{Defaults to \dQuote{CCF}.}
+    \item{ylab.label}{Defaults to \dQuote{SNV Density}.}
+    \item{xlimits}{Limits for the x-axis. Defaults to \code{c(0, 1.5)}.}
+    \item{xat}{Positions for the x-axis labels. Defaults to \code{seq(0, 1.5, 0.25)}.}
+    \item{legend.size}{Width of the legend boxes in 'character' units. Defaults to 3}
+    \item{legend.title.cex}{Size of titles in the legends. Defaults to 1.2}
+    \item{legend.label.cex}{Size of text labels in the legends. Defaults to 1}
+    \item{legend.x}{x position of the legend. Defaults to 0.8}
+    \item{legend.y}{y position of the legend. Defaults to 0.9}
+    \item{height}{Height of the plot. Defaults to 6}
+    \item{width}{Width of the plot. Defaults to 10}
+    \item{size.units}{Units for the height and width. Defaults to \dQuote{in}.}
+    \item{resolution}{Resolution of the plot. Defaults to 1000}
+    \item{...}{Pass through argument. See BoutrosLab.plotting.general::create.histogram() for further details.}
+}
+\value{A `grob` object of the heatmap.}
+\author{Helena Winata}
+\seealso{\code{\link[BoutrosLab.plotting.general]{create.histogram}}, \code{\link[BoutrosLab.plotting.general]{create.scatterplot}}}

man/create.cluster.heatmap.Rd

@@ -22,6 +22,7 @@ create.cluster.heatmap(
     xaxis.fontface = 'bold',
     y.spacing = 1,
     colour.scheme = c('white', 'blue'),
+    plot.objects.heights = c(1, 0.2),
     ...
     );
 }
@@ -42,6 +43,7 @@ create.cluster.heatmap(
     \item{xaxis.fontface}{Defaults to \dQuote{bold}.}
     \item{y.spacing}{Spacing between heatmap and clone covariate bar. Defaults to 1}
     \item{colour.scheme}{Colour scheme for the heatmap. Defaults to \code{c('white', 'blue')}.}
+    \item{plot.objects.heights}{Object heights. Defaults to \code{c(1, 0.2)}.}
     \item{...}{Pass through argument. See BoutrosLab.plotting.general::create.heatmap() for further details.}
 }
 \value{A `grob` object of the heatmap.}