R/419-extractPCMMDSScales.R
extractPCMMDSScales.Rd
Generalized Scales-Based Descriptors derived by Multidimensional Scaling
extractPCMMDSScales(x, propmat, k, lag, scale = TRUE, silent = TRUE)
x | A character vector, as the input protein sequence. |
---|---|
propmat | A matrix containing the properties for the amino acids. Each row represent one amino acid type, each column represents one property. Note that the one-letter row names must be provided for we need them to seek the properties for each AA type. |
k | Integer. The maximum dimension of the space which the data are to be represented in. Must be no greater than the number of AA properties provided. |
lag | The lag parameter. Must be less than the amino acids. |
scale | Logical. Should we auto-scale the property matrix
( |
silent | Logical. Whether we print the |
A length lag * p^2
named vector,
p
is the number of scales (dimensionality) selected.
This function calculates the generalized scales-based descriptors derived by Multidimensional Scaling (MDS). Users could provide customized amino acid property matrices.
Venkatarajan, M. S., & Braun, W. (2001). New quantitative descriptors of amino acids based on multidimensional scaling of a large number of physical-chemical properties. Molecular modeling annual, 7(12), 445--453.
See extractPCMScales
for generalized scales-based
descriptors derived by Principal Components Analysis.
# NOT RUN { x = readFASTA(system.file('protseq/P00750.fasta', package = 'Rcpi'))[[1]] data(AATopo) tprops = AATopo[, c(37:41, 43:47)] # select a set of topological descriptors mds = extractPCMMDSScales(x, propmat = tprops, k = 5, lag = 7, silent = FALSE) # }