filter.cmap | R Documentation |
This function filters a tridimensional contact matrix (NxNxZ), where N is the residue number and Z is the simulation number) selecting only contacts present in at least P simulations.
filter.cmap(cm, cutoff.sims = NULL)
cm |
An array of dimensions NxNxZ or a list of NxN matrices
containing binary contact values as obtained from
|
cutoff.sims |
A single element numeric vector corresponding to the minimum number of simulations a contact between two residues must be present. If not, it will be set to 0 in the output matrix. |
The output matrix is a nXn binary matrix (n = residue number). Elements equal to 1 correspond to residues in contact, elements equal to 0 to residues not in contact.
cmap
, plot.cmap
## Not run:
## load example data
pdbfile <- system.file("examples/hivp.pdb", package="bio3d")
pdb <- read.pdb(pdbfile)
trtfile <- system.file("examples/hivp.dcd", package="bio3d")
trj <- read.dcd(trtfile, verbose=FALSE)
## split the trj example in two
num.of.frames <- dim(trj)[1]
trj1 <- trj[1:(num.of.frames/2),]
trj2 <- trj[((num.of.frames/2)+1):num.of.frames,]
## Lets work with Calpha atoms only
ca.inds <- atom.select(pdb, "calpha")
#noh.inds <- atom.select(pdb, "noh")
## calculate single contact map matrices
cms <- list()
cms[[1]] <- cmap(trj1[,ca.inds$xyz], pcut=0.3, scut=0, dcut=7, mask.lower=FALSE)
cms[[2]] <- cmap(trj1[,ca.inds$xyz], pcut=0.3, scut=0, dcut=7, mask.lower=FALSE)
## calculate average contact matrix
cm.filter <- filter.cmap(cms, cutoff.sims=2)
## plot the result
par(pty="s", mfcol=c(1,3))
plot.cmap(cms[[1]])
plot.cmap(cms[[2]])
plot.cmap(cm.filter)
## End(Not run)
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