Add group annotation strips to a tidyHeatmap — annotation

`annotation_group()` adds group annotation strips to a tidyHeatmap object, allowing you to visually group rows or columns based on categorical variables. This is useful for highlighting biological or experimental groups in your heatmap.

annotation_group(.data, ...)

# S4 method for class 'InputHeatmap'
annotation_group(
  .data,
  ...,
  palette_grouping = list(),
  group_label_fontsize = 8,
  show_group_name = FALSE,
  group_strip_height = grid::unit(9, "pt")
)

Source

[Mangiola and Papenfuss., 2020](https://joss.theoj.org/papers/10.21105/joss.02472)

Arguments

.data: A tidyHeatmap object
...: Grouping columns (unquoted, like dplyr::group_by)
palette_grouping: List of color vectors for each grouping. Each element should be a vector of colors for the corresponding grouping variable.
group_label_fontsize: Font size for group labels
show_group_name: Logical, show the group annotation name
group_strip_height: Height of group strip as a grid unit (default: 9pt)

Value

A tidyHeatmap object with group annotation strips added

References

Mangiola, S. and Papenfuss, A.T., 2020. "tidyHeatmap: an R package for modular heatmap production based on tidy principles." Journal of Open Source Software. doi:10.21105/joss.02472.

Examples


# Basic usage with row grouping
tidyHeatmap::N52 |>
  tidyHeatmap::heatmap(
    .row = symbol_ct,
    .column = UBR,
    .value = `read count normalised log`
  ) |>
  annotation_group(CAPRA_TOTAL)


# With custom colors and formatting
tidyHeatmap::N52 |>
  tidyHeatmap::heatmap(
    .row = symbol_ct,
    .column = UBR,
    .value = `read count normalised log`
  ) |>
  annotation_group(
    CAPRA_TOTAL,
    palette_grouping = list(c("#E64B35", "#4DBBD5")),
    group_label_fontsize = 10,
    show_group_name = FALSE
  )


# Multiple grouping variables
tidyHeatmap::N52 |>
  tidyHeatmap::heatmap(
    .row = symbol_ct,
    .column = UBR,
    .value = `read count normalised log`
  ) |>
  annotation_group(
    CAPRA_TOTAL, 
    `Cell type`,
    palette_grouping = list(
      c("#E64B35", "#4DBBD5"),  # colors for CAPRA_TOTAL
      c("#00A087", "#F39B7F")   # colors for Cell type
    )
  )