rmsip {bio3d} | R Documentation |
Root Mean Square Inner Product
Description
Calculate the RMSIP between two mode subspaces.
Usage
rmsip(...)
## S3 method for class 'enma'
rmsip(enma, ncore=NULL, subset=10, ...)
## Default S3 method:
rmsip(modes.a, modes.b, subset=10,
row.name="a", col.name="b", ...)
Arguments
enma |
an object of class |
ncore |
number of CPU cores used to do the calculation.
|
subset |
the number of modes to consider. |
modes.a |
an object of class |
modes.b |
an object of class |
row.name |
prefix name for the rows. |
col.name |
prefix name for the columns. |
... |
arguments passed to associated functions. |
Details
RMSIP is a measure for the similarity between two set of modes obtained from principal component or normal modes analysis.
Value
Returns an rmsip
object with the following components:
overlap |
a numeric matrix containing pairwise (squared) dot products between the modes. |
rmsip |
a numeric RMSIP value. |
For function rmsip.enma
a numeric matrix containing all
pairwise RMSIP values of the modes stored in the enma
object.
Author(s)
Lars Skjaerven
References
Skjaerven, L. et al. (2014) BMC Bioinformatics 15, 399. Grant, B.J. et al. (2006) Bioinformatics 22, 2695–2696. Amadei, A. et al. (1999) Proteins 36, 19–424.
See Also
Other similarity measures:
sip
, covsoverlap
,
bhattacharyya
.
Examples
## Not run:
# Load data for HIV example
trj <- read.dcd(system.file("examples/hivp.dcd", package="bio3d"))
pdb <- read.pdb(system.file("examples/hivp.pdb", package="bio3d"))
# Do PCA on simulation data
xyz.md <- fit.xyz(pdb$xyz, trj, fixed.inds=1:ncol(trj))
pc.sim <- pca.xyz(xyz.md)
# NMA
modes <- nma(pdb)
# Calculate the RMSIP between the MD-PCs and the NMA-MODEs
r <- rmsip(modes, pc.sim, subset=10, row.name="NMA", col.name="PCA")
# Plot pairwise overlap values
plot(r, xlab="NMA", ylab="PCA")
## End(Not run)