bio3d (version 2.3-4)

dccm.enma: Cross-Correlation for Ensemble NMA (eNMA)

Description

Calculate the cross-correlation matrices from an ensemble of NMA objects.

Usage

# S3 method for enma
dccm(x, ncore = NULL, na.rm=FALSE, …)

Arguments

x

an object of class enma as obtained from function nma.pdbs.

ncore

number of CPU cores used to do the calculation. ncore>1 requires package ‘parallel’ installed.

na.rm

logical, if FALSE the DCCM might containt NA values (applies only when the enma object is calculated with argument ‘rm.gaps=FALSE’).

…

additional arguments passed to dccm.nma.

Value

Returns a list with the following components:

all.dccm

an array or list containing the correlation matrices for each ‘nma’ object. An array is returned when the ‘enma’ object is calculated with ‘rm.gaps=TRUE’, and a list is used when ‘rm.gaps=FALSE’.

avg.dccm

a numeric matrix containing the average correlation matrix. The average is only calculated when the ‘enma’ object is calculated with ‘rm.gaps=TRUE’.

Details

This is a wrapper function for calling dccm.nma on a collection of ‘nma’ objects as obtained from function nma.pdbs.

See examples for more details.

References

Wynsberghe. A.W.V, Cui, Q. Structure 14, 1647--1653. Grant, B.J. et al. (2006) Bioinformatics 22, 2695--2696.

See Also

nma, dccm.nma, plot.dccm

Examples

# NOT RUN {
## Needs MUSCLE installed - testing excluded

if(check.utility("muscle")) {

## Fetch PDB files and split to chain A only PDB files
ids <- c("1a70_A", "1czp_A", "1frd_A", "1fxi_A", "1iue_A", "1pfd_A")
files <- get.pdb(ids, split = TRUE, path = tempdir())

## Sequence/Structure Alignement
pdbs <- pdbaln(files, outfile = tempfile())

## Normal mode analysis on aligned data
modes <- nma(pdbs)

## Calculate all 6 correlation matrices
cij <- dccm(modes)

## Plot correlations for first structure
plot.dccm(cij$all.dccm[,,1])

}
# }
# NOT RUN {
# }