Plot network heatmap

Plot network heatmap

plot_network_heatmap(
  network_table,
  regulators = NULL,
  targets = NULL,
  switch_matrix = TRUE,
  show_names = FALSE,
  heatmap_size_lock = TRUE,
  heatmap_size = 5,
  heatmap_height = NULL,
  heatmap_width = NULL,
  heatmap_title = NULL,
  heatmap_color = c("#1966ad", "white", "#bb141a"),
  border_color = "gray",
  rect_color = NA,
  anno_width = 1,
  anno_height = 1,
  row_anno_type = NULL,
  column_anno_type = NULL,
  legend_name = "Weight",
  row_title = "Regulators"
)

Arguments

network_table

The weight data table of network.

regulators

Regulators list.

targets

Targets list.

switch_matrix

Logical value, default is TRUE, whether to weight data table to matrix.

show_names

Logical value, default is FALSE, whether to show names of row and column.

heatmap_size_lock

Lock the size of heatmap.

heatmap_size

Default is 5. The size of heatmap.

heatmap_height

The height of heatmap.

heatmap_width

The width of heatmap.

heatmap_title

The title of heatmap.

heatmap_color

Colors of heatmap.

border_color

Default is gray. Color of heatmap border.

rect_color

Default is NA. Color of heatmap rect.

anno_width

Width of annotation.

anno_height

Height of annotation.

row_anno_type

Default is NULL, could add a annotation plot to row, choose one of boxplot, barplot, histogram, density, lines, points, and horizon.

column_anno_type

Default is NULL, could add a annotation plot to column, choose one of boxplot, barplot, histogram, density, lines, and points.

legend_name

The name of legend.

row_title

The title of row.

Value

A heatmap

Examples

data("example_matrix")
data("example_ground_truth")
network_table <- inferCSN(example_matrix)
#> ✔ Running for <dense matrix>.
#> ✔ Checking input parameters.
#> ✔ Using L0 sparse regression model.
#> ✔ Using 1 core.
#> ✔ Run done.

p1 <- plot_network_heatmap(
  example_ground_truth[, 1:3],
  heatmap_title = "Ground truth",
  legend_name = "Ground truth"
)
p2 <- plot_network_heatmap(
  network_table,
  heatmap_title = "inferCSN",
  legend_name = "inferCSN"
)
ComplexHeatmap::draw(p1 + p2)


p3 <- plot_network_heatmap(
  network_table,
  heatmap_title = "inferCSN",
  legend_name = "Weight1",
  heatmap_color = c("#20a485", "#410054", "#fee81f")
)
p4 <- plot_network_heatmap(
  network_table,
  heatmap_title = "inferCSN",
  legend_name = "Weight2",
  heatmap_color = c("#20a485", "white", "#fee81f")
)
ComplexHeatmap::draw(p3 + p4)


plot_network_heatmap(
  network_table,
  show_names = TRUE,
  rect_color = "gray90",
  row_anno_type = "density",
  column_anno_type = "barplot"
)


plot_network_heatmap(
  network_table,
  regulators = c("g1", "g2"),
  show_names = TRUE
)


plot_network_heatmap(
  network_table,
  targets = c("g1", "g2"),
  row_anno_type = "boxplot",
  column_anno_type = "histogram",
  show_names = TRUE
)


plot_network_heatmap(
  network_table,
  regulators = c("g1", "g3", "g5"),
  targets = c("g3", "g6", "g9"),
  show_names = TRUE
)