Prune A cna Network Object

Remove nodes and their associated edges from a cna network graph.

prune.cna(x, edges.min = 1, size.min = 1)

Arguments

x	A protein network graph object as obtained from the ‘cna’ function.
edges.min	A single element numeric vector specifying the minimum number of edges that retained nodes should have. Nodes with less than ‘edges.min’ will be pruned.
size.min	A single element numeric vector specifying the minimum node size that retained nodes should have. Nodes with less composite residues than ‘size.min’ will be pruned.

Details

This function is useful for cleaning up cna network plots by removing, for example, small isolated nodes. The output is a new cna object minus the pruned nodes and their associated edges. Node naming is preserved.

Value

A cna class object, see function cna for details.

References

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

Author

Barry Grant

Note

Some improvements to this function are required, including a better effort to preserve the original community structure rather than calculating a new one. Also may consider removing nodes form the raw.network object that is returned also.

Examples


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

# Load the correlation network
attach(hivp)

# Read the starting PDB file to determine atom correspondence
pdbfile <- system.file("examples/hivp.pdb", package="bio3d")
pdb <- read.pdb(pdbfile)

# Plot coarse grain network based on dynamically coupled communities
par(mfcol=c(1,2), mar=c(0,0,0,0))
plot.cna(net)

# Prune network
dnet <- prune.cna(net, edges.min = 1)
plot(dnet)

detach(hivp)

}
#> Obtaining estimated layout with fruchterman.reingold
#>  id size                      members
#>   1   24      c(1:4, 94:107, 193:198)
#>   2    4                          5:8
#>   3   22               c(9:23, 64:70)
#>   4    4                        24:27
#>   5    2                        28:29
#>   6   49              c(30:63, 71:85)
#>   7    1                           86
#>   8    1                           87
#>   9    2                        88:89
#>  10    4                        90:93
#>  11   20 c(108:113, 117:122, 163:170)
#>  12   50 c(114:116, 129:162, 171:183)
#>  13    4                      123:126
#>  14    2                      127:128
#>  15    1                          184
#>  16    2                      185:186
#>  17    2                      187:188
#>  18    4                      189:192
#> Removing Nodes: 7, 8, 9, 16, 17 
#> id	size	edges	members
#> 7	1	0	86
#> 8	1	0	87
#> 9	2	0	88:89
#> 16	2	0	185:186
#> 17	2	0	187:188
#> Obtaining estimated layout with fruchterman.reingold