network.amendment. bio3d 2.3-0

Usage

network.amendment(x, membership, minus.log=TRUE)

Arguments

x: A protein network graph object as obtained from the ‘cna’ function.
membership: A numeric vector containing the new community membership.
minus.log: Logical. Whether to use the minus.log on the cij values.

Description

This function changes the ‘communities’ attribute of a ‘cna’ class object to match a given membership vector.

Value

Returns a ‘cna’ class object with the attributes changed according to the membership vector provided.

Details

This function is useful, in combination with ‘community.tree’, for inspecting different community partitioning options of a input ‘cna’ object. See examples.

Examples


# PDB server connection required - testing excluded

##-- Build a CNA object
pdb <- read.pdb("4Q21")

  Note: Accessing on-line PDB file

modes <- nma(pdb)

 Building Hessian...		Done in 0.067 seconds.
 Diagonalizing Hessian...	Done in 0.277 seconds.

cij <- dccm(modes)


  |======================================================================| 100%

net <- cna(cij, cutoff.cij=0.2)

##-- Community membership vector for each clustering step
tree <- community.tree(net, rescale=TRUE)

## Produce a new k=7 membership vector and CNA network
memb.k7 <- tree$tree[ tree$num.of.comms == 7, ]
net.7 <- network.amendment(net, memb.k7)

plot(net.7, pdb)

Obtaining layout from PDB structure


print(net)



Call:
  cna.dccm(cij = cij, cutoff.cij = 0.2)

Structure: 
 - NETWORK NODES#:   168 	EDGES#: 668 
 - COMMUNITY NODES#: 9 	EDGES#: 19 

 + attr: network, communities, community.network,
        community.cij, cij, call

print(net.7)


Call:
  cna.dccm(cij = cij, cutoff.cij = 0.2)

Structure: 
 - NETWORK NODES#:   168 	EDGES#: 668 
 - COMMUNITY NODES#: 7 	EDGES#: 13 

 + attr: network, communities, community.network,
        community.cij, cij, call

Author

Guido Scarabelli

Amendment of a CNA Network According To A Input Community Membership Vector.