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Performs principal components analysis (PCA) on an ensemble of PDB structures.
# S3 method for pdbs pca(pdbs, core.find = FALSE, fit = FALSE, ...)
Returns a list with the following components:
eigenvalues.
eigenvectors (i.e. the variable loadings).
scores of the supplied data on the pcs.
data
the standard deviations of the pcs.
the means that were subtracted.
an object of class pdbs as obtained from function pdbaln or read.fasta.pdb.
pdbs
pdbaln
read.fasta.pdb
logical, if TRUE core.find() function will be called to find core positions and coordinates of PDB structures will be fitted based on cores.
logical, if TRUE coordinates of PDB structures will be fitted based on all CA atoms.
additional arguments passed to the method pca.xyz.
pca.xyz
Barry Grant, Lars Skjaerven and Xin-Qiu Yao
The function pca.pdbs is a wrapper for the function pca.xyz, wherein more details of the PCA procedure are documented.
pca.pdbs
Grant, B.J. et al. (2006) Bioinformatics 22, 2695--2696.
pca, pca.xyz, pdbaln, nma.
pca
nma
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)
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