Project Data onto Principal Components

Projects data onto principal components.

project.pca(data, pca, angular = FALSE, fit = FALSE, ...)
z2xyz.pca(z.coord, pca)
xyz2z.pca(xyz.coord, pca)

Arguments

data	a numeric vector or row-wise matrix of data to be projected.
pca	an object of class "pca" as obtained from functions pca.xyz or pca.tor.
angular	logical, if TRUE the data to be projected is treated as torsion angle data.
fit	logical, if TRUE the data is first fitted to pca$mean.
...	other parameters for fit.xyz.
xyz.coord	a numeric vector or row-wise matrix of data to be projected.
z.coord	a numeric vector or row-wise matrix of PC scores (i.e. the z-scores which are centered and rotated versions of the origional data projected onto the PCs) for conversion to xyz coordinates.

Value

A numeric vector or matrix of projected PC scores.

References

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

Author

Karim ElSawy and Barry Grant

See also

pca.xyz, pca.tor, fit.xyz

Examples

if (FALSE) {
attach(transducin)

gaps.pos <- gap.inspect(pdbs$xyz)

#-- Do PCA without structures 2 and 7
pc.xray <- pca.xyz(pdbs$xyz[-c(2,7), gaps.pos$f.inds])

#-- Project structures 2 and 7 onto the PC space
d <- project.pca(pdbs$xyz[c(2,7), gaps.pos$f.inds], pc.xray)

plot(pc.xray$z[,1], pc.xray$z[,2],col="gray")
points(d[,1],d[,2], col="red")

detach(transducin)
}