plot.modules: Visualization of large biological networks.

Description

Modular layout style:

Visualization of graphs in a modular form.

Usage

"plot"(x, layout.function=NULL,mod.list=NULL, 
module.function=FALSE, split.graph=7, color.random=FALSE,
modules.color = NULL, col.grad=NULL, mod.edge.col=NULL,
ed.color=NULL,edge.col.random=FALSE, expression = NULL,
exp.by.module=FALSE, tkplot=FALSE, layout.overall = NULL,
sf=0,arrange.bydegree=FALSE,mod.lab=FALSE,node.lab=FALSE,
lab.cex = NULL,lab.color=NULL, lab.dist=NULL, v.size=FALSE,
nodeset=NULL,path.col="green", col.s1="red", col.s2="yellow",
nodes.on.path=TRUE,e.path.width=c(1,1),
scale.module=NULL,v.sf=5,e.width=.5,bg="black",
abstract.graph=TRUE, modules.name.num = TRUE, v.size.path=TRUE,...)

Arguments

x is a graph object created from an adjacency matrix or from a tabular data of two columns using graph() function available in igraph

layout.function

is a 'function' class or a vector of functions to plot the layout of each module by a function in 'layout.function'.

mod.list

mod.list is a list object, which provides a modular information about the graph, each components of mod.list contains a vector of nodes to be plotted.

module.function

is a logical value for obtaining modules in the network.

random

is a boolean variable, if 'mod.list' is null, it picks the nodes for modules randomly.

split.graph

split.graph if random is TRUE, it provides no. of modules that a graph to be split.

color.random

If this option is TRUE it will assign random colors to modules.

modules.color

Is a vector of colors to assign a color to each module by the the user.

col.grad

is a vector of colors or can be a list of vectors of colors to assign the colors to the nodes for each modules based on their degree from low to high.

mod.edge.col

is a vector of color to assign the edge color to the edges of a modules.

ed.color

is a scaler of color and assign colors to the edges between modules.

edge.col.random

is a boolean variable and assign colors to the edges of each module randomly.

expression

expression is a numeric vector which represents properties of genes or proteins like mean expression values or p-values, If this option is given, the nodes are colored with a range of colors from red to blue (red for low expression, blue for high expression) depending on the expression values.

exp.by.module

this option is a boolean or a numeric vector which represents the order of modules given as an input in the mod.list option. This option is used to see the variation in expression values of nodes in a particular module by using a range of color from red to blue, red indicate low expression value and blue indicates high expression values.

tkplot

it is a boolean variable, if it is true, function will use 'tkplot' function to plot a graph, if it is false function will use plot function with the black background.

layout.overall

this option belongs to the class 'function', for this option any function which returns a two column matrix which should have rows equal to the no of modules for the placement of the modules.

is an integer variable is used to scale up or scale down the graph plot.

arrange.bydegree

is a boolean variable; if true the coordinates of nodes are assigned by their degree, higher degree nodes are plotted towards center and lower degree nodes are plotted outside.

mod.lab

is a boolean variable; prints module labels at center of each module if the module's names are available in 'mod.list' as list names.

node.lab

is a boolean variable; this option plots the vertex label, if option is TRUE.

lab.cex

is a numeric variable; this determines the size of the label of the vertices or the modules.

lab.color

is a string variable; this assigns colors to the label of vertices or the modules.

lab.dist

is a numeric variable; this adjusts vertices label.

nodeset

is a list object contains two vector, it can be a numeric vector also. First vector contains set of start nodes and second vector contains end nodes. In the case of numeric vector which indicates the module id, it is used to show shortest path between two modules. Shortest paths are visualized between start nodes and end nodes.

path.col

is a color vector for coloring the shortest path between start nodes and end nodes.

col.s1

is a color vector to color start nodes or modules.

col.s2

is a color vector to color end nodes or modules.

nodes.on.path

is a logical value which shows nodes which connect start nodes and end nodes.

e.path.width

is a vector containing of size 2. This option sets the edge width of the shortest paths between two modules or two set of nodes.

scale.module

is a numeric vector of the size of total number of modules. This option scales the size of each module independently.

v.size

is a numeric value or a numeric vector which contains numeric values to assign the size of nodes.

e.width

is a numeric value to assign the width to edges.

v.sf

is a numeric value. This is used to adjust vertex size when v.size input is a numeric vector.

is a color value to adjust background color of the plot.

abstract.graph

is a logical value which adjusts the abstract view of modular plot using force-based algorithm or any input function given in layout.overall option.

modules.name.num

is a logical value for displaying module name or its number

v.size.path

is a numeric or logical value which adjusts the size of nodes between which the shortest path to be shown.

...

... parameter for other inputs.

Value

returns a list object of 'netbiov' class

References

http://bio-complexity.com/

Examples

Run this code

  data("PPI_Athalina")
  data("modules_PPI_Athalina")

  ## Example 1 #######%
  ##% Modular layout plot of A. Thalina PPI network, modules 
##are colored randomly, module information is given as a list 
##object ###%
  id <- plot.modules(g1,mod.list = lm, 
layout.function=layout.graphopt, color.random = TRUE , 
tkplot=FALSE,node.lab=FALSE,v.size=1)

  ## Example 2 #######%
  ##% Modular layout plot of A. Thalina PPI network, modules 
##are colored randomly, module information is  predicted using 
##'fastgreedy' algorithm ###%
  id <- plot.modules(g1, layout.function=layout.graphopt, 
color.random = TRUE , tkplot=FALSE,node.lab=FALSE,v.size=1)

  ## Example 3 #######%
  ##% Modular layout plot of A. Thalina PPI network when 
##expression value of genes are given ###%
  id <- plot.modules(g1, layout.function=layout.graphopt, 
color.random = TRUE, expression=rnorm(vcount(g1)), 
tkplot=FALSE,node.lab=FALSE,v.size=1)
  
  ## Example 4 #######%
  ##% Modular layout plot of A. Thalina PPI network when 
##expression value of modules 1, 2 and 3 are shown by colors by
##ranking independently from each other ###%
  id <- plot.modules(g1, layout.function=layout.graphopt, 
modules.color="grey", expression=rnorm(vcount(g1)), 
tkplot=FALSE,node.lab=FALSE,v.size=1, exp.by.module=c(1,2,3))

  ## Example 5 #######%
  ##% Modular layout plot of A. Thalina PPI network by 
##emphasizing module labels ###%
  id <- plot.modules(g1, mod.list=lm, 
layout.function=layout.graphopt, modules.color="grey", 
tkplot=FALSE, mod.lab=TRUE,v.size=1, lab.color="green" )

  ## Example 6 #######%
  ##% Modular layout plot of A. Thalina PPI network 
##highlighting shortest paths between modules 1, 5 and 7, 18 ###%
  id <- plot.modules(g1, mod.list=lm, 
layout.function=layout.graphopt, modules.color="grey", 
tkplot=FALSE, nodeset=c(1,5,7,18), sf=-10, v.size=1)  

  ## Example 7 #######%
  ##% Modular layout plot of A. Thalina PPI network combining 
##two layouts ###%
  fn <- function(g)layout.star(g, 
center=which.max(degree(g))-1)
  id <- plot.modules(g1,mod.list = lm, 
layout.function=layout.graphopt, layout.overall=fn, color.random 
= TRUE , tkplot=FALSE,node.lab=FALSE,v.size=1)

  ## Example 8 #######%
  ##% Modular layout plot of A. Thalina PPI network by scaling 
##up second module and scaling down the expansion of other modules ###%
  fn <- function(g)layout.star(g, 
center=which.max(degree(g))-1)
  sm <- rep(1, length(lm))
  sm[2] <- 40
  id <- plot.modules(g1,mod.list = lm, layout.function=layout.graphopt,
layout.overall=fn, color.random=TRUE,tkplot=FALSE,v.size=2, scale.module=sm, 
mod.edge.col="green")