mem_multienrichplot | R Documentation |
MultiEnrichMap plot
mem_multienrichplot(
mem,
overlap = 0.1,
overlap_count = 2,
do_plot = TRUE,
do_legend = TRUE,
remove_blanks = TRUE,
remove_singlets = TRUE,
spread_labels = TRUE,
y_bias = 1,
label_edges = c("overlap_count", "count", "overlap", "label", "none"),
edge_cex = 1,
node_cex = 0.8,
node_size = 5,
edge_color = "#55555588",
frame_color = "#55555500",
shape = "pie",
repulse = 3.7,
sets = NULL,
rescale = TRUE,
edge_bundling = "connections",
main = "MultiEnrichMap\noverlap >= {overlap}, overlap_count >= {overlap_count}",
...
)
mem |
|
overlap |
numeric value between 0 and 1, indicating the Jaccard
overlap filter to use for edge nodes. The value is used to
delete edges whose values |
overlap_count |
numeric value indicating the minimum overlap count
below which edges are removed. The value |
do_plot |
logical indicating whether to plot the final result. |
do_legend |
logical indicating whether to print a color legend,
valid when |
remove_blanks |
logical indicating whether to call
|
remove_singlets |
logical indicating whether to remove singlet
nodes, which are nodes that have no connections to other nodes.
By default, singlets are removed, in order to help visualize the
node connections that remain after filtering by |
spread_labels |
logical indicating whether to call
|
y_bias |
numeric value passed to |
repulse |
numeric value used for network layout when
|
sets |
optional character vector of enriched sets to include,
all other sets will be excluded. These values are matched with
|
rescale |
logical indicating whether the |
main |
character string used as the title when |
... |
additional arguments are passed to |
This function is likely to be replaced by mem2emap()
.
This function takes output from multiEnrichMap()
and produces
customized "multiple enrichMap" plots using an igraph network.
It differs from the data provided from multiEnrichMap()
mostly
by enabling different overlap filters, and by automating
several steps that help with network layout, and node label
placement.
For the most flexible exploration of data, run multiEnrichMap()
using a lenient overlapThreshold
, for example overlapThreshold=0.1
.
Then call this function with increasing overlap
until the
visualization has insightful structure.
invisibly returns the igraph
object used for plotting,
a by-product of this function when do_plot=TRUE
is that
the igraph object is also visualized. All custom plot elements
are updated in the igraph
object, so in principle a
simple call to plot(...)
should suffice.
Other jam igraph functions:
cnet2df()
,
cnet2im()
,
cnetplotJam()
,
cnetplot_internalJam()
,
color_edges_by_nodegroups()
,
color_edges_by_nodes_deprecated()
,
color_edges_by_nodes()
,
color_nodes_by_nodegroups()
,
communities2nodegroups()
,
drawEllipse()
,
edge_bundle_bipartite()
,
edge_bundle_nodegroups()
,
enrichMapJam()
,
fixSetLabels()
,
flip_edges()
,
get_bipartite_nodeset()
,
igraph2pieGraph()
,
jam_igraph()
,
jam_plot_igraph()
,
label_communities()
,
layout_with_qfrf()
,
layout_with_qfr()
,
mem2emap()
,
memIM2cnet()
,
nodegroups2communities()
,
rectifyPiegraph()
,
relayout_with_qfr()
,
removeIgraphBlanks()
,
removeIgraphSinglets()
,
reorderIgraphNodes()
,
rotate_igraph_layout()
,
spread_igraph_labels()
,
subgraph_jam()
,
subsetCnetIgraph()
,
subset_igraph_components()
,
sync_igraph_communities()
,
with_qfr()
Other jam plot functions:
adjust_polygon_border()
,
grid_with_title()
,
jam_igraph()
,
mem_enrichment_heatmap()
,
mem_gene_path_heatmap()
,
mem_legend()
,
mem_plot_folio()
,
plot_layout_scale()
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