netAnalysis_diff_signalingRole_scatter: 2D visualization of differential signaling roles (dominant...

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

2D visualization of differential signaling roles (dominant senders (sources) or receivers (targets) ) of each cell group when comparing mutiple datasets

Description

This scatter plot shows the differential signaling roles (dominant senders (sources) or receivers (targets) in a 2D space.

x-axis and y-axis are respectively the differential outgoing or incoming communication probability associated with each cell group. Dot colors indicate different cell groups. Dot shapes indicate different categories of cell groups if 'group“ is defined.

Positive values indicate the increase in the second dataset while negative values indicate the increase in the first dataset

Usage

netAnalysis_diff_signalingRole_scatter(
  object,
  color.use = NULL,
  comparison = c(1, 2),
  signaling = NULL,
  signaling.exclude = NULL,
  idents.exclude = NULL,
  slot.name = "netP",
  group = NULL,
  dot.size = 2.5,
  point.shape = c(21, 22, 24, 23, 25, 8, 3),
  label.size = 3,
  dot.alpha = 0.6,
  x.measure = "outdeg",
  y.measure = "indeg",
  xlabel = "Outgoing interaction strength",
  ylabel = "Incoming interaction strength",
  title = NULL,
  font.size = 10,
  font.size.title = 10,
  do.label = T,
  show.legend = T,
  show.axes = T
)

Arguments

object	A merged CellChat object of a list of CellChat objects
color.use	defining the color for each cell group
comparison	an index vector giving the two datasets for comparison
signaling	a char vector containing signaling pathway names. signaling = NULL: Signaling role analysis on the aggregated cell-cell communication network from all signaling pathways
signaling.exclude	signaling pathways to exclude
idents.exclude	cell groups to exclude. This is useful when zooming into the small changes
slot.name	the slot name of object that is used to compute centrality measures of signaling networks
group	a vector to categorize the cell groups, e.g., categorize the cell groups into two major categories: immune cells and fibroblasts
dot.size	the size of the symbol
point.shape	point shape when group is not NULL
label.size	font size of the text
dot.alpha	transparency
x.measure	The measure used as x-axis. This measure should be one of 'names(slot(object, slot.name)$centr[[1]])' computed from 'netAnalysis_computeCentrality' Default = "outdeg" is the weighted outgoing links (i.e., Outgoing interaction strength). If setting as "outdeg_unweighted", it represents the total number of outgoing signaling.
y.measure	The measure used as y-axis. This measure should be one of 'names(slot(object, slot.name)$centr[[1]])' computed from 'netAnalysis_computeCentrality' Default = "indeg" is the weighted incoming links (i.e., Incoming interaction strength). If setting as "indeg_unweighted", it represents the total number of incoming signaling.
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

Value

ggplot object

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