Cluster-wise Heatmap of Missing Data Patterns

Visualize the pattern of missing values in a dataset, arranged by cluster. Each column in the heatmap represents one observation and each row a feature. Tiles indicate whether a value is missing (black) or present (white). Cluster labels are shown as a column annotation bar above the heatmap. The package ComplexHeatmap must be installed for this function to work.

Usage

cluster_heatmap(
  data,
  clusters,
  cols_ignore = NULL,
  show_row_names = TRUE,
  missing_color = "black",
  observed_color = "white",
  title = "Missingness Heatmap by Cluster"
)

Arguments

data

A data.frame or tibble containing the dataset with possible missing values. Rows represent observations and columns represent features.

clusters

A vector of cluster labels for each observation (row) in data. Must have the same length as nrow(data).

cols_ignore

Optional character vector of column names in data to exclude from the heatmap (e.g., identifiers or non-feature columns).

show_row_names

Logical. If TRUE, displays feature names on plot

missing_color

Display color of missing values. Default black.

observed_color

Display color of observed values. Default white.

title

Optional plot title. Defaults to "Missingness Heatmap by Cluster"

Value

A list of class "ComplexHeatmap" containing the heatmap object. This can be used for further inspection or manual redraw.

Details

This function constructs a binary missingness matrix where 1 indicates a missing value and 0 a present value. Columns (observations) are ordered by their cluster labels, and the function displays a heatmap of missingness patterns using ComplexHeatmap. Cluster membership is displayed as an annotation above the heatmap.

Examples

if(requireNamespace("ComplexHeatmap")){
# Simple example with small dataset
df <- data.frame(
  x1 = c(1, NA, 3),
  x2 = c(NA, 2, 3),
  x3 = c(1, 2, NA)
)
cl <- c("A", "B", "A")
cluster_heatmap(df, cl)

# Example excluding a column prior to plotting
cluster_heatmap(df, cl, cols_ignore = "x2")

# Adding a 'Cluster' label and changing colors
cluster_heatmap(df, clusters = paste0("Cluster ", cl), cols_ignore = "x2", 
missing_color = "red", observed_color = "blue")
}