Plot cluster centre profiles as a heatmap

Cluster centres across clustering variables. Values are the centres in the frozen analysis scale, so a centred and scaled model reads directly as standard deviations from the cohort mean.

PlotClusterCentreProfile() shows the same centres as connected lines, which reads more like the SOM line map when variables have a meaningful order.

Usage

PlotClusterCentreHeatmap(
  centers,
  variable_labels = NULL,
  title = "Cluster centre profiles",
  value_label = "Centre"
)

PlotClusterCentreProfile(
  centers,
  variable_labels = NULL,
  title = "Cluster centre profiles",
  value_label = "Centre"
)

Arguments

centers

Matrix or data frame of cluster centres, one row per cluster.

variable_labels

Optional display labels for the columns.

title

Plot title.

value_label

Legend title describing the centre scale.

Value

A ggplot object, or NULL when centres are unavailable.

Examples

# \donttest{
data(SimulatedPhenotypeData)
df_Training <- dplyr::filter(SimulatedPhenotypeData, .data$Cohort == "Training")
model <- CreateClusterModel_KMeans(
  df_Training, paste0("Var", 1:12), method = "finalize", final_k = 4
)
model$ModelInfo$plots$centre_heatmap

# }