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Create clustered expression dendrogram

Source: R/plot_dendrogram.R
create_cluster_dendrogram.Rd

Create a dendrogram based on a data.table with columns for cluster ID, variables, and their values. If no specific values are provided for the 'col' params then they will be assumed as 1. clus_col, 2. var_col, 3. val_col

Usage

create_cluster_dendrogram(
  data,
  clus_col = names(data)[[1]],
  var_col = names(data)[[2]],
  val_col = names(data)[[3]],
  cor = c("pearson", "spearman"),
  distance = "ward.D",
  h = NULL,
  h_color = "red",
  rotate = FALSE,
  ...
)

Arguments

data

data.table. Should include columns with clustering labels, variables that are being clustered, and the values of those clusters.

clus_col

character. name of column with clustering info

var_col

character. name of column with variable name

val_col

character. name of column with values info

cor

correlation score to calculate distance (e.g. "pearson", "spearman")

distance

distance method to use for hierarchical clustering, default to "ward.D"

h

height of horizontal lines to plot

h_color

color of horizontal lines

rotate

rotate dendrogram 90 degrees

...

Arguments passed on to ggdendro::ggdendrogram

segments

If TRUE, show line segments

labels

if TRUE, shows segment labels

leaf_labels

if TRUE, shows leaf labels

theme_dendro

if TRUE, applies a blank theme to plot (see theme_dendro())

Value

ggdendrogram

Examples

g <- GiottoData::loadGiottoMini("visium", verbose = FALSE)

g_expression <- head(GiottoClass::getExpression(g, output = "matrix"))
g_expression_df <- as.data.frame(as.matrix(g_expression))
g_expression_df$feat_ID <- rownames(g_expression)

g_expression_melt <- data.table::melt(g_expression_df, id.vars = "feat_ID",
measure.vars = colnames(g_expression), variable.name = "cell_ID",
value.name = "raw_expression")
#> Warning: The melt generic in data.table has been passed a data.frame and will attempt to redirect to the relevant reshape2 method; please note that reshape2 is superseded and is no longer actively developed, and this redirection is now deprecated. To continue using melt methods from reshape2 while both libraries are attached, e.g. melt.list, you can prepend the namespace, i.e. reshape2::melt(g_expression_df). In the next version, this warning will become an error.

create_cluster_dendrogram(data.table::as.data.table(g_expression_melt),
var_col = "cell_ID", clus_col = "feat_ID", "raw_expression")
#> Error in loadNamespace(x): there is no package called ‘ggdendro’