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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)
#> 
#> 1. use installGiottoEnvironment() to install
#>  a local miniconda python environment along with required modules
#> 
#> 2. provide an existing python path to
#>  python_path to use your own python path which has all modules
#>  installed
#> Set options("giotto.use_conda" = FALSE) if
#>  python functionalities are not needed

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 <- reshape2::melt(g_expression_df, id.vars = "feat_ID", 
measure.vars = colnames(g_expression), variable.name = "cell_ID", 
value.name = "raw_expression")

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’