CCC heatmap and dot matrix plot

Usage

CCCHeatmap(
  srt,
  method = NULL,
  condition = NULL,
  dataset = 1,
  comparison = c(1, 2),
  plot_type = c("heatmap", "dot", "bubble", "ligand_target", "role_heatmap",
    "diff_heatmap"),
  display_by = c("aggregation", "interaction"),
  sender.use = NULL,
  receiver.use = NULL,
  ligand.use = NULL,
  receptor.use = NULL,
  interaction.use = NULL,
  signaling = NULL,
  pairLR.use = NULL,
  slot.name = "net",
  thresh = 0.05,
  measure = c("count", "weight"),
  pattern = c("outgoing", "incoming", "all"),
  value = "sum",
  top_n = 500,
  top_anno = "bar",
  right_anno = "cell",
  left_anno = "bar",
  bottom_anno = "cell",
  bar_value = "sum",
  add_text = NULL,
  cluster_rows = FALSE,
  cluster_columns = FALSE,
  color.by = c("score", "pvalue"),
  x_text_angle = 90,
  facet_by = NULL,
  show_row_names = TRUE,
  show_column_names = TRUE,
  edge_value = c("sum", "mean", "max", "count"),
  border = TRUE,
  value_palette = "RdBu",
  value_palcolor = NULL,
  cell_palette = "Chinese",
  cell_palcolor = NULL,
  palette = "Chinese",
  palcolor = NULL,
  width = NULL,
  height = NULL,
  units = "inch",
  title = NULL,
  subtitle = NULL,
  legend.position = "right",
  legend.direction = "vertical",
  font.size = 10,
  theme_use = "theme_scop",
  theme_args = list(),
  verbose = TRUE,
  ...
)

Arguments

srt: A Seurat object.
method: Communication result type to use.
condition: Result name or comparison name.
dataset: Dataset index or name.
comparison: Comparison indices or names.
plot_type: Plot type. One of "heatmap" or "dot". "bubble" is a CellChat-specific interaction bubble matrix. "ligand_target" is a special heatmap path available only with NicheNet/MultiNicheNet results. "role_heatmap" and "diff_heatmap" are CellChat-specific pathway role views.
display_by: Whether to summarize by "aggregation" or "interaction".
sender.use: Sender cell types to keep.
receiver.use: Receiver cell types to keep.
ligand.use: Ligands to keep.
receptor.use: Receptors to keep.
interaction.use: Interaction names to keep.
signaling: Signaling pathway to focus on.
pairLR.use: Specific ligand-receptor pair(s) to keep.
slot.name: CellChat slot name.
thresh: Significance threshold used when extracting communication results.
measure: Summary measure for CellChat objects.
pattern: Pattern used for pathway role plots.
value: Value column or summary statistic to use.
top_n: Number of top records to retain.
top_anno, bottom_anno: Column-side annotations for sender groups. Each side accepts NULL, "bar", "box", "point", "line", "histogram", "density", "violin", "cell", or a character vector containing multiple values. Defaults are top_anno = "bar" and bottom_anno = "cell".
left_anno, right_anno: Row-side annotations for receiver groups. Each side accepts NULL, "bar", "box", "point", "line", "histogram", "density", "violin", "cell", or a character vector containing multiple values. Defaults are left_anno = "bar" and right_anno = "cell".
bar_value: Aggregation metric shown in the bar annotations. One or more of "count", "sum", "mean", or "max". Multiple values add multiple annotation tracks. Default "sum".
add_text: Logical. Show numeric value labels inside each cell (heatmap mode only). Default TRUE for aggregation mode, FALSE for interaction mode.
cluster_rows, cluster_columns: Whether to cluster heatmap rows/columns. Defaults are both FALSE.
color.by: For interaction heatmaps, value used for tile coloring. Usually "score" or "pvalue".
x_text_angle: Rotation angle for x-axis labels.
facet_by: Faceting variable for interaction-level plots.
show_row_names, show_column_names: Whether to draw row/column names for the heatmap body.
edge_value: Aggregation statistic for network edges.
border: Logical. Whether to draw borders for the heatmap body and all annotation tracks. Default TRUE.
value_palette: Palette used for heatmap value fills.
value_palcolor: Optional custom colors for value_palette.
cell_palette: Cell annotation palette name.
cell_palcolor: Custom cell annotation colors.
palette: Main palette name.
palcolor: Main custom palette colors.
width, height: Optional heatmap body width and height. When only one is supplied, the other is inferred from the matrix dimensions to keep cells square. When both are NULL, a square-cell size is computed automatically.
units: Units for width and height. Default "inch".
title: Plot title.
subtitle: Plot subtitle.
legend.position: Legend position.
legend.direction: Legend direction.
font.size: Base font size.
theme_use: Theme function used for styling.
theme_args: Arguments passed to the theme function.
verbose: Whether to print messages.
...: Additional plot-specific options.

Value

A ggplot / patchwork object wrapping the ComplexHeatmap grob.

Examples

if (FALSE) { # \dontrun{
data(pancreas_sub)
pancreas_sub <- standard_scop(pancreas_sub)

pc1 <- Seurat::Embeddings(pancreas_sub, "Standardpca")[, 1]
ct <- as.character(pancreas_sub$CellType)
ct_medians <- tapply(pc1, ct, median)
pancreas_sub$Condition <- ifelse(
  pc1 > ct_medians[ct],
  "ConditionA",
  "ConditionB"
)

pancreas_sub <- RunCellChat(
  pancreas_sub,
  group.by = "CellType",
  group_column = "Condition",
  group_cmp = list(c("ConditionA", "ConditionB")),
  species = "Mus_musculus"
)

CCCHeatmap(
  pancreas_sub,
  method = "CellChat",
  condition = "ConditionA",
  plot_type = "dot",
  display_by = "aggregation",
  top_n = 20
)

CCCHeatmap(
  pancreas_sub,
  method = "CellChat",
  condition = "ConditionA",
  plot_type = "dot",
  display_by = "interaction",
  facet_by = "sender",
  top_n = 20
)

CCCHeatmap(
  pancreas_sub,
  method = "CellChat",
  condition = "ConditionA",
  plot_type = "dot",
  display_by = "interaction",
  facet_by = "receiver",
  top_n = 20
)

CCCHeatmap(
  pancreas_sub,
  method = "CellChat",
  condition = "ConditionA",
  plot_type = "heatmap",
  display_by = "aggregation",
  top_n = 20
)

CCCHeatmap(
  pancreas_sub,
  method = "CellChat",
  condition = "ConditionA",
  plot_type = "heatmap",
  display_by = "interaction",
  facet_by = "sender",
  top_n = 10
)

CCCHeatmap(
  pancreas_sub,
  method = "CellChat",
  condition = "ConditionA",
  plot_type = "heatmap",
  display_by = "interaction",
  facet_by = "sender",
  color.by = "pvalue",
  top_n = 10
)

CCCHeatmap(
  pancreas_sub,
  method = "CellChat",
  condition = "ConditionA",
  plot_type = "bubble",
  top_n = 5
)

CCCHeatmap(
  pancreas_sub,
  method = "CellChat",
  condition = "ConditionA_vs_ConditionB",
  plot_type = "bubble",
  top_n = 5
)

CCCHeatmap(
  pancreas_sub,
  method = "CellChat",
  condition = "ConditionA",
  plot_type = "role_heatmap",
  #' pattern = "outgoing",
  width = 0.6,
  height = 2.5
)

CCCHeatmap(
  pancreas_sub,
  method = "CellChat",
  condition = "ConditionA",
  plot_type = "role_heatmap",
  pattern = "outgoing",
  width = 0.6,
  height = 2.5
)

CCCHeatmap(
  pancreas_sub,
  method = "CellChat",
  condition = "ConditionA_vs_ConditionB",
  plot_type = "role_heatmap",
  pattern = "incoming",
  palette = "Paired",
  width = 0.6,
  height = 3.5
)

CCCHeatmap(
  pancreas_sub,
  method = "CellChat",
  condition = "ConditionA_vs_ConditionB",
  plot_type = "diff_heatmap",
  pattern = "all",
  palette = "Paired",
  top_n = 20,
  width = 0.6,
  height = 3.5
)
} # }