Make a clustering dendrogram with coloring by experimental variable

A simple function using ggdendro to make a sample dendrogram

Usage

clustering_dendrogram(
  plotmatrix,
  experiment,
  colorby = NULL,
  cor_method = "pearson",
  cluster_method = "ward.D",
  plot_title = "",
  labelspace = 0.2,
  palette = NULL,
  palette_name = COLORBLIND_PALETTE_NAME
)

Arguments

plotmatrix: Expression/ other data matrix
experiment: Annotation for the columns of plotmatrix
colorby: Column name in experiment specifying how boxes should be colored
cor_method: Correlation method, passed to cor() (default: pearson).
cluster_method: Clustering method, passed to hclust() (default: ward.D).
plot_title: Plot title
labelspace: Vertical fraction of plot to be used for labels (default: 0.2).
palette: Palette of colors, one for each unique value derived from colorby.
palette_name: Valid R color palette name

Value

output A ggplot output

Examples

# Make a dendrogram with the data in airway

require(airway)
data(airway, package = "airway")
clustering_dendrogram(assays(airway)[[1]], data.frame(colData(airway)), colorby = "dex")


# Do the same, but only usig the 1000 most variant rows and see how the
# clustering improves.

mymatrix <- assays(airway)[[1]]
mymatrix <- mymatrix[order(apply(mymatrix, 1, var), decreasing = TRUE)[1:1000], ]
clustering_dendrogram(mymatrix, data.frame(colData(airway)), colorby = "dex")