mem_enrichment_heatmap | R Documentation |
MultiEnrichment Heatmap of enrichment P-values
mem_enrichment_heatmap(
mem,
style = c("dotplot_inverted", "dotplot", "heatmap"),
apply_direction = FALSE,
p_cutoff = mem$p_cutoff,
min_count = 1,
p_floor = 1e-10,
point_size_factor = 1,
point_size_max = 8,
point_size_min = 2,
row_method = "euclidean",
column_method = "euclidean",
name = "-log10P",
row_dend_reorder = TRUE,
row_dend_width = grid::unit(30, "mm"),
row_fontsize = NULL,
row_cex = 1,
row_split = NULL,
row_gap = grid::unit(2, "mm"),
cluster_rows = TRUE,
column_fontsize = NULL,
column_cex = 1,
cluster_columns = FALSE,
sets = NULL,
color_by_column = FALSE,
cex.axis = 1,
lens = 3,
cexCellnote = 1,
column_title = NULL,
row_names_max_width = grid::unit(300, "mm"),
column_names_max_height = grid::unit(300, "mm"),
heatmap_legend_param = NULL,
hm_cell_size = NULL,
legend_height = grid::unit(6, "cm"),
legend_cex = 1,
direction_cutoff = 0,
gene_count_max = NULL,
top_annotation = NULL,
outline = TRUE,
show_enrich = NULL,
use_raster = FALSE,
do_plot = TRUE,
...
)
mem |
|
style |
|
apply_direction |
|
p_cutoff |
|
min_count |
|
p_floor |
|
point_size_factor |
|
point_size_min , point_size_max |
|
row_method |
|
name |
|
row_dend_reorder |
|
row_fontsize , column_fontsize |
optional |
cluster_columns |
|
sets |
|
color_by_column |
|
cex.axis |
|
lens |
|
cexCellnote |
|
column_title |
optional |
row_names_max_width , column_names_max_height , heatmap_legend_param |
arguments passed to |
hm_cell_size |
|
legend_height |
|
legend_cex |
|
top_annotation |
|
outline |
|
show_enrich |
|
use_raster |
|
do_plot |
|
... |
additional arguments are passed to |
Note: It is recommended to call mem_plot_folio()
with do_which=1
in order to utilize the gene-pathway content during clustering,
which is more effective at clustering similar pathways by gene
content. Otherwise pathways are clustered using only the
-log10(p)
enrichment P-value.
This function is a lightweight wrapper to ComplexHeatmap::Heatmap()
intended to visualize the enrichment P-values from multiple
enrichment results. The P-value threshold is used to colorize
every cell whose P-value meets the threshold, while all other
cells are therefore white.
The style
argument controls whether a heatmap or dotplot is
created.
style="dotplot"
: each heatmap cell is not filled, and the color
is drawn as a circle with size proportional to the number of
genes involved in enrichment. A separate point legend is returned
as an attribute of the heatmap object.
style="dotplot_inverted"
: each heatmap cell is filled, and
a circle is drawn with size proportional to the number of
genes involved in enrichment. A separate point legend is returned
as an attribute of the heatmap object.
To draw the dotplot heatmap including the point legend, use this command:
ComplexHeatmap::draw(hm, annotation_legend_list=attr(hm, "annotation_legend_list"))
Generally, the clustering using the gene-pathway incidence matrix is more effective at representing biologically-driven pathway clusters.
Other jam plot functions:
adjust_polygon_border()
,
grid_with_title()
,
jam_igraph()
,
mem_gene_path_heatmap()
,
mem_legend()
,
mem_multienrichplot()
,
mem_plot_folio()
,
plot_layout_scale()
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