dccm.enma. bio3d 2.3-0

Usage

"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.

Description

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

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.

Value

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’.

References

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

Examples


## Needs MUSCLE installed - testing excluded


## 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())


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


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

Reading PDB files:
/tmp/RtmpTDihxb/split_chain/1a70_A.pdb
/tmp/RtmpTDihxb/split_chain/1czp_A.pdb
/tmp/RtmpTDihxb/split_chain/1frd_A.pdb
/tmp/RtmpTDihxb/split_chain/1fxi_A.pdb
/tmp/RtmpTDihxb/split_chain/1iue_A.pdb
/tmp/RtmpTDihxb/split_chain/1pfd_A.pdb
.   PDB has ALT records, taking A only, rm.alt=TRUE
.....

Extracting sequences

pdb/seq: 1   name: /tmp/RtmpTDihxb/split_chain/1a70_A.pdb 
pdb/seq: 2   name: /tmp/RtmpTDihxb/split_chain/1czp_A.pdb 
   PDB has ALT records, taking A only, rm.alt=TRUE
pdb/seq: 3   name: /tmp/RtmpTDihxb/split_chain/1frd_A.pdb 
pdb/seq: 4   name: /tmp/RtmpTDihxb/split_chain/1fxi_A.pdb 
pdb/seq: 5   name: /tmp/RtmpTDihxb/split_chain/1iue_A.pdb 
pdb/seq: 6   name: /tmp/RtmpTDihxb/split_chain/1pfd_A.pdb 


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


Details of Scheduled Calculation:
  ... 6 input structures 
  ... storing 282 eigenvectors for each structure 
  ... dimension of x$U.subspace: ( 288x282x6 )
  ... coordinate superposition prior to NM calculation 
  ... aligned eigenvectors (gap containing positions removed)  
  ... estimated memory usage of final 'eNMA' object: 3.7 Mb 


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


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

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

Author

Lars Skjaerven

Cross-Correlation for Ensemble NMA (eNMA)