extractPCMScales {Rcpi} | R Documentation

## Generalized Scales-Based Descriptors derived by Principal Components Analysis

### Description

Generalized Scales-Based Descriptors derived by Principal Components Analysis

### Usage

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

### Arguments

`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.
`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 we print the standard deviation, proportion of variance and the cumulative proportion of the selected principal components or not. Default is `TRUE`.

### Details

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

### Value

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

### Author(s)

Nan Xiao <https://nanx.me>

### See Also

See `extractPCMDescScales` for generalized AA property based scales descriptors, and `extractPCMPropScales` for (19 classes) AA descriptor based scales descriptors.

### Examples

    x = readFASTA(system.file('protseq/P00750.fasta', package = 'Rcpi'))[[1]]
    data(AAindex)
    AAidxmat = t(na.omit(as.matrix(AAindex[, 7:26])))
    scales = extractPCMScales(x, propmat = AAidxmat, pc = 5, lag = 7, silent = FALSE)

[Package Rcpi version 1.30.0 Index]