plot_tf_network: Function to visualize transcription factors regulatory...

View source: R/network_visualization.R

plot_tf_networkR Documentation

Function to visualize transcription factors regulatory network

Description

This function integrate R package igraph to visualize consequence of regulatory network analysis

Usage

plot_tf_network(
  TFs_list,
  layout = "grid",
  group.cols = NULL,
  title.name = NULL,
  vertex.size = 13,
  vertex.size.add = 3,
  vertex.label.color = "black",
  edge.label.color = "black",
  legend = TRUE,
  vertex.label.cex = 0.8,
  vertex.label.family = "ArialMT",
  frame.color = "white",
  arrow.size = 0.2,
  arrow.width = 0.5,
  edge.width = 1.8,
  edge.curved = 0,
  edge.color = c("#FDD1B0", "#B3B3B3")
)

Arguments

TFs_list

TFs_list generated by network_analysis

layout

the layout to display the network, options: 'grid','sphere', 'circle','random'

group.cols

colors for group in network

title.name

the name of the title

vertex.size

size of vertex whose edge numbers are last 25%

vertex.size.add

expansion size of vertex whose edge numbers are last 25%-75% and top25%

vertex.label.color

ertex label color

edge.label.color

edge label color

legend

logic, indicating whether to show the legend

vertex.label.cex

The label size of vertex

vertex.label.family

vertex label family

frame.color

frame.color

arrow.size

arrow size

arrow.width

arrow width

edge.width

edge width

edge.curved

edge curvature

edge.color

edge color. You need to input two colors, first one indicate 'Positive' regulation, second one indicate 'Negative' regulation.

Value

figure

Examples

#'
load(system.file("extdata", "test_clustering.rda", package = "IReNA"))
Kmeans_clustering <- add_ENSID(test_clustering, Spec1 = "Hs")
cor0.6 <- get_cor(Kmeans_clustering, Tranfac201803_Hs_MotifTFsF, 0.7, start_column=3)
TFs_list <- network_analysis(cor0.6,Kmeans_clustering)
plot_tf_network(TFs_list)

jiang-junyao/IReNA documentation built on May 2, 2024, 6:54 a.m.