add function to create ccf densityplot

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
+        ));
+    }