rmsf.Rd
Calculate atomic root mean squared fluctuations.
rmsf(xyz, grpby=NULL, average=FALSE)
xyz | numeric matrix of coordinates with each row corresponding to an individual conformer. |
---|---|
grpby | a vector counting connective duplicated elements that indicate the elements of 'xyz' that should be considered as a group (e.g. atoms from a particular residue). If provided a 'pdb' object, grouping is automatically set by amino acid residues. |
average | logical, if TRUE averaged over atoms. |
RMSF is an often used measure of conformational variance. It is calculated by
$$f_i=\sqrt{\frac{1}{M-1}\sum_j \|r_i^j-r_i^0\|^2}$$,
where \(f_i\) is the RMSF value for the ith atom, M the total number of frames
(total number of rows of xyz
), \(r_i^j\) the positional vector of the
ith atom in the jth frame, and \(r_i^0\) the mean position of ith atom.
||r|| denotes the Euclidean norm of the vector r.
Returns a numeric vector of RMSF values. If average=TRUE
a single numeric value
representing the averaged RMSF value over all atoms will be returned.
Grant, B.J. et al. (2006) Bioinformatics 22, 2695--2696.
Barry Grant
read.dcd
, fit.xyz
,
read.fasta.pdb
attach(transducin) # Ignore Gaps gaps <- gap.inspect(pdbs$ali) r <- rmsf(pdbs$xyz) plot(r[gaps$f.inds], typ="h", ylab="RMSF (A)")detach(transducin) if (FALSE) { pdb <- read.pdb("1d1d", multi=TRUE) xyz <- pdb$xyz # superimpose trajectory xyz <- fit.xyz(xyz[1, ], xyz) # select mainchain atoms sele <- atom.select(pdb, elety=c("CA", "C", "N", "O")) # residue numbers to group by resno <- pdb$atom$resno[sele$atom] # mean rmsf value of mainchain atoms of each residue r <- rmsf(xyz[, sele$xyz], grpby=resno) plot.bio3d(r, resno=pdb, sse=pdb, ylab="RMSF (A)") }