extractScalesGap: Scales-Based Descriptors derived by Principal Components Analysis (with Gap Support)

Description

This function calculates scales-based descriptors derived by Principal Components Analysis (PCA), with gap support. Users can provide customized amino acid property matrices. This function implements the core computation procedure needed for the scales-based descriptors derived by AA-Properties (AAindex) and scales-based descriptors derived by 20+ classes of 2D and 3D molecular descriptors (Topological, WHIM, VHSE, etc.) in the protr package.

Usage

extractScalesGap(x, propmat, pc, lag, scale = TRUE, silent = TRUE)

Value

A length lag * p^2 named vector, p is the number of scales (principal components) selected.

Arguments

x: A character vector, as the input protein sequence. Use '-' to represent gaps in the 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.
pc: Integer. Use the first pc principal components as the scales. 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 (propmat) before PCA? Default is TRUE.
silent: Logical. Whether to print the standard deviation, proportion of variance and the cumulative proportion of the selected principal components or not. Default is TRUE.

Author

Nan Xiao <https://nanx.me>

Examples

Run this code

# amino acid sequence with gaps
x <- readFASTA(system.file("protseq/align.fasta", package = "protr"))$`IXI_235`
data(AAindex)
AAidxmat <- t(na.omit(as.matrix(AAindex[, 7:26])))
scales <- extractScalesGap(x, propmat = AAidxmat, pc = 5, lag = 7, silent = FALSE)