Performs principal components analysis (PCA) on torsion angle data.

# S3 method for tor
pca(data, ...)

Arguments

data numeric matrix of torsion angles with a row per structure. additional arguments passed to the method pca.xyz.

Value

Returns a list with the following components:

L

eigenvalues.

U

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.

Author

Barry Grant and Karim ElSawy

torsion.xyz, plot.pca, plot.pca.loadings, pca.xyz
##-- PCA on torsion data for multiple PDBs
gaps.pos <- gap.inspect(pdbs$xyz) tor <- t(apply( pdbs$xyz[, gaps.pos$f.inds], 1, torsion.xyz, atm.inc=1)) pc.tor <- pca.tor(tor[,-c(1,233,234,235)]) #plot(pc.tor) plot.pca.loadings(pc.tor) detach(kinesin) if (FALSE) { ##-- PCA on torsion data from an MD trajectory trj <- read.dcd( system.file("examples/hivp.dcd", package="bio3d") ) tor <- t(apply(trj, 1, torsion.xyz, atm.inc=1)) gaps <- gap.inspect(tor) pc.tor <- pca.tor(tor[,gaps$f.inds])