bio3d (version 2.1-2)

pca.pdbs: Principal Component Analysis

Description

Performs principal components analysis (PCA) on an ensemble of PDB structures.

Usage

## S3 method for class 'pdbs':
pca(pdbs, core.find = FALSE, fit = FALSE, \dots)

Arguments

pdbs

an object of class pdbs as obtained from function pdbaln or read.fasta.pdb.

core.find

logical, if TRUE core.find() function will be called to find core positions and coordinates of PDB structures will be fitted based on cores.

fit

logical, if TRUE coordinates of PDB structures will be fitted based on all CA atoms.

...

additional arguments passed to the method pca.xyz.

Value

• Returns a list with the following components:
• L
  eigenvalues.
• U
  eigenvectors (i.e. the variable loadings).
• z.u
  scores of the supplied data on the pcs.
• sdev
  the standard deviations of the pcs.
• mean
  the means that were subtracted.

Details

The function pca.pdbs is a wrapper for the function pca.xyz, wherein more details of the PCA procedure are documented.

References

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

See Also

pca, pca.xyz, pdbaln, nma.

Examples

attach(transducin)

#-- Do PCA ignoring gap containing positions
pc.xray <- pca(pdbs)

# Plot results (conformer plots & scree plot)
plot(pc.xray, col=annotation[, "color"])