R: DCCM: Dynamical Cross-Correlation Matrix

dccm {bio3d} | R Documentation

## DCCM: Dynamical Cross-Correlation Matrix

### Description

Determine the cross-correlations of atomic displacements.

### Usage

    dccm(x, ...)

### Arguments

`x` | a numeric matrix of Cartesian coordinates with a row per structure/frame which will br passed to `dccm.xyz()`. Alternatively, an object of class `nma` as obtained from function `nma` that will be passed to the `dccm.nma()` function, see below for examples.
`...` | additional arguments passed to the methods `dccm.xyz`, `dccm.pca`, `dccm.nma`, and `dccm.enma`.

### Details

`dccm` is a generic function calling the corresponding function determined by the class of the input argument `x`. Use `methods("dccm")` to get all the methods for `dccm` generic:

`dccm.xyz` will be used when `x` is a numeric matrix containing Cartesian coordinates (e.g. trajectory data).

`dccm.pca` will calculate the cross-correlations based on an `pca` object.

`dccm.nma` will calculate the cross-correlations based on an `nma` object. Similarly, `dccm.enma` will calculate the correlation matrices based on an ensemble of `nma` objects (as obtained from function `nma.pdbs`).

`plot.dccm` and `pymol.dccm` provides convenient functionality to plot a correlation map, and visualize the correlations in the structure, respectively.

See examples for each corresponding function for more details.

### Author(s)

Barry Grant, Lars Skjaerven

### References

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

### See Also

`dccm.xyz`, `dccm.nma`, `dccm.enma`, `dccm.pca`, `plot.dccm`, `pymol.dccm`.

[Package bio3d version 2.3-3 Index]