netVisual_embedding: 2D visualization of the learned manifold of signaling...

In sqjin/CellChat: Inference and analysis of cell-cell communication from single-cell and spatial transcriptomics data

2D visualization of the learned manifold of signaling networks

Description

2D visualization of the learned manifold of signaling networks

Usage

netVisual_embedding(
  object,
  slot.name = "netP",
  type = c("functional", "structural"),
  color.use = NULL,
  pathway.labeled = NULL,
  top.label = 1,
  pathway.remove = NULL,
  pathway.remove.show = TRUE,
  dot.size = c(2, 6),
  label.size = 2,
  dot.alpha = 0.5,
  xlabel = "Dim 1",
  ylabel = "Dim 2",
  title = NULL,
  font.size = 10,
  font.size.title = 12,
  do.label = T,
  show.legend = T,
  show.axes = T
)

Arguments

object	CellChat object
slot.name	the slot name of object that is used to compute centrality measures of signaling networks
type	"functional","structural"
color.use	defining the color for each cell group
pathway.labeled	a char vector giving the signaling names to show when labeling each point
top.label	the fraction of signaling pathways to label
pathway.remove	a character vector defining the signaling to remove
pathway.remove.show	whether show the removed signaling names
dot.size	a range defining the size of the symbol
label.size	font size of the text
dot.alpha	transparency
xlabel	label of x-axis
ylabel	label of y-axis
title	main title of the plot
font.size	font size of the text
font.size.title	font size of the title
do.label	label the each point
show.legend	whether show the legend
show.axes	whether show the axes

sqjin/CellChat documentation built on Nov. 10, 2023, 4:29 a.m.