plot.cna {bio3d}

Protein Structure Network Plots in 2D and 3D.

Description

Plot a protein dynamic network as obtained from the cna function.

Usage

  ## S3 method for class 'cna'
plot(x, pdb = NULL, weights=NULL, vertex.size=NULL,
            layout=NULL, col=NULL, full=FALSE, scale=TRUE, color.edge = FALSE, 
            interactive=FALSE, ...)
  ## S3 method for class 'ecna'
plot(x, ...)

Arguments

x

A protein network graph object (or a list of such objects) as obtained from the ‘cna’ function.

pdb

A PDB structure object obtained from ‘read.pdb’. If supplied this will be used to guide the network plot ‘layout’, see ‘layout.cna’ for details.

weights

A numeric vector containing the edge weights for the network.

vertex.size

A numeric vector of node/community sizes. If NULL the size will be taken from the input network graph object ‘x’. Typically for ‘full=TRUE’ nodes will be of an equal size and for ‘full=FALSE’ community node size will be proportional to the residue membership of each community.

layout

Either a function or a numeric matrix. It specifies how the vertices will be placed on the plot. See ‘layout.cna’.

col

A vector of colors used for node/vertex rendering. If NULL these values are taken from the input network ‘V(x$community.network)$color’.

full

Logical, if TRUE the full all-atom network rather than the clustered community network will be plotted.

scale

Logical, if TRUE weights are scaled with respect to the network.

color.edge

Logical, if TRUE edges are colored with respect to their weights.

interactive

Logical, if TRUE interactive graph will be drawn where users can manually adjust the network (positions of vertices, colors of edges, etc.). Needs Tcl/Tk support in the installed R build.

...

Additional graphical parameters for ‘plot.igraph’.

Details

This function calls ‘plot.igraph’ from the igraph package to plot cna networks the way we like them.

The plot layout is user settable, we like the options of: ‘layout.cna’, ‘layout.fruchterman.reingold’, ‘layout.mds’ or ‘layout.svd’. Note that first of these uses PDB structure information to produce a more meaningful layout.

Extensive plot modifications are possible by setting additional graphical parameters (...). These options are detailed in ‘igraph.plotting’. Common parameters to alter include:

vertex.label:

Node labels, V(x$network)$name. Use NA to omit.

vertex.label.color:

Node label colors, see also vertex.label.cex etc.

edge.color:

Edge colors, E(x$network)$color.

mark.groups:

Community highlighting, a community list object, see also mark.col etc.

Value

Produces a network plot on the active graphics device. Also returns the plot layout coordinates silently, which can be passed to the ‘identify.cna’ function.

Note

Be sure to check the correspondence of your ‘pdb’ object with your network object ‘x’, as few internal checks are currently performed by the ‘layout.cna’ function.

Author(s)

Barry Grant and Guido Scarabelli

References

Grant, B.J. et al. (2006) Bioinformatics 22, 2695–2696.

See Also

plot.igraph, plot.communities, igraph.plotting

Examples

# PDB server connection required - testing excluded

if (!requireNamespace("igraph", quietly = TRUE)) {
   message('Need igraph installed to run this example')
} else {

##-- Build a CNA object
pdb <- read.pdb("4Q21")
modes <- nma(pdb)
cij <- dccm(modes)
net <- cna(cij, cutoff.cij=0.2)

# Plot coarse grain network based on dynamically coupled communities
xy <- plot.cna(net)
#plot.dccm(cij, margin.segments=net$communities$membership)

# Chose a different PDB informed layout for plot
plot.cna(net, pdb)

# Play with plot layout and colors...
plot.cna(net, layout=igraph::layout.mds(net$community.network), col=c("blue","green") ) 

# Plot full residue network colored by communities - will be slow due to number of edges!!
plot.cna(net, pdb, full=TRUE)

# Alter plot settings
plot.cna(net, pdb, full=TRUE, vertex.size=3, weights=1, vertex.label=NA)

}