scapGNN (version 0.1.4)

plotCCNetwork: Visualize cell cluster association network graph

Description

The plotCCNetwork function takes cells belonging to the same phenotype as a cluster. When cell phenotypes are not provided, the plotCCNetwork functions identify cell clusters based on edge betweenness. Cell interactions between cell clusters are merged into one edge by mean. The thickness of the edge indicates the strength of interaction between cell clusters.

Usage

plotCCNetwork(
  network.data,
  cell_id = NULL,
  cell_cluster = FALSE,
  cluster_method = "louvain",
  vertex.colors = NULL,
  vertex.size = 10,
  vertex.label.cex = 0.8,
  vertex.label.dist = 1,
  vertex.label.color = "black",
  edge.width = 5,
  margin = 0,
  layout = layout_with_lgl,
  legend.cex = 1.5,
  legend.pt.cex = 3,
  proportion = 1,
  plotgraph = TRUE
)

Value

Graph or network data.

Arguments

network.data

The input network data is the result from the ConNetGNN function.

cell_id

A vector of cell phenotype.Methods include louvain (default), leading eigen and edge betweenness.

cell_cluster

A binary value. Whether to automatically identify cell clusters based on edge betweenness. Default: FALSE.

cluster_method

Community structure detection method

vertex.colors

The fill color of the vertex. The number of colors should match the number of cell phenotypes. If NULL (default), the system will automatically assign colors.

vertex.size

The size of the vertex. Default: 10.

vertex.label.cex

The font size for vertex labels. Default: 0.8.

vertex.label.dist

The distance of the label from the center of the vertex. If it is 0 then the label is centered on the vertex. Default: 1.

vertex.label.color

The color of the labels. Default: black.

edge.width

The width of the edge. This does not affect the relative size of the edge weights. Default: 5.

margin

The amount of empty space below, over, at the left and right of the plot, it is a numeric vector of length four. Usually values between 0 and 0.5 are meaningful, but negative values are also possible, that will make the plot zoom in to a part of the graph. If it is shorter than four then it is recycled. Default: 0.

layout

Either a function or a numeric matrix. It specifies how the vertices will be placed on the plot. For details, please refer to the igraphPackage. Default: layout_with_lgl.

legend.cex

The font size of legend. Default: 1.5.

legend.pt.cex

Expansion factor(s) for the points. Default: 3.

proportion

This parameter specifies what percentage of edges to display (edges are sorted by their weight in descending order). Default: 1, all edges are used.

plotgraph

Whether to draw the picture. Default: TRUE. If FALSE, the image will not be displayed but the network data will be returned in the igraph data format.

Details

plotCCNetwork

Examples

require(igraph)
require(graphics)

data(ConNetGNN_data)

# Construct the cell phenotype vector.
cell_id<-colnames(ConNetGNN_data[["cell_network"]])
temp<-unlist(strsplit(cell_id,"_"))
cell_phen<-temp[seq(2,length(temp)-1,by=3)]
names(cell_id)<-cell_phen
head(cell_id)
plotCCNetwork(ConNetGNN_data,cell_id,edge.width=10)