R/418-extractPCMFAScales.R
extractPCMFAScales.Rd
Generalized Scales-Based Descriptors derived by Factor Analysis
extractPCMFAScales(x, propmat, factors, scores = "regression", 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. |
factors | Integer. The number of factors to be fitted. Must be no greater than the number of AA properties provided. |
scores | Type of scores to produce. The default is |
lag | The lag parameter. Must be less than the amino acids number in the protein sequence. |
scale | Logical. Should we auto-scale the property matrix
( |
silent | Logical. Whether we print the SS loadings,
proportion of variance and the cumulative proportion of
the selected factors or not.
Default is |
A length lag * p^2
named vector,
p
is the number of scales (factors) selected.
This function calculates the generalized scales-based descriptors derived by Factor Analysis (FA). Users could provide customized amino acid property matrices.
Atchley, W. R., Zhao, J., Fernandes, A. D., & Druke, T. (2005). Solving the protein sequence metric problem. Proceedings of the National Academy of Sciences of the United States of America, 102(18), 6395-6400.
# 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 fa = extractPCMFAScales(x, propmat = tprops, factors = 5, lag = 7, silent = FALSE) # }