Principal Component Analysis

Usage

"pca"(pdbs, core.find = FALSE, fit = FALSE, ...)

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.

Description

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

Details

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

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.

References

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

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"])

detach(transducin)

See also

pca, pca.xyz, pdbaln, nma.

Author

Barry Grant, Lars Skjaerven and Xin-Qiu Yao